Original Research Archives

Budget impact analysis of a rituximab intravenous biosimilar in patients with follicular lymphoma and large B-cell non-Hodgkin lymphoma in Chile

Posted on March 21, 2024

Author byline as per print journal: Tomás Abbot¹, MSc; Nicolás Armijo¹, MSc; Robin Piron², PhD; Manuel Espinoza^1,3, PhD

Introduction: In Chile, access disparities and budget constraints affect the treatment of non-Hodgkin lymphoma patients, even though therapies like rituximab are covered by the Regime of Explicit Health Guarantees. Biosimilars like Rixathon® off er a compelling alternative with similar efficacy at lower cost. This study conducted a budget impact analysis to assess the introduction of Rixathon® for follicular lymphoma (FL) and diff use large B-cell non-Hodgkin lymphoma (DLBCL) patients from Chilean healthcare system perspective.
Methods: A budget impact model was developed to estimate the cost difference between the actual scenario and a scenario considering greater Rixathon® coverage over a five-year period. Annual population was estimated based on rituximab sales data from 2015–2022 adjusted with corresponding factors. This study focused on differences in the total sum of acquisition and administration costs. Several scenarios were developed and analysed, including time-driven activity-based costing (TDABC) to estimate administration costs.
Results: The projected population increases from 1,274 to 1,297 individuals for 2023–2027. Scenario 1 demonstrated that Rixathon® generated net cost savings of US$208,553 in 2023, or US$6,728 per patient, potentially enabling 49 additional patients to access Rixathon®. Similar trends are observed in Scenarios 2 and 3. The TDABC analysis revealed that the increment in administration costs were offset by the savings achieved through Rixathon® acquisition.
Conclusion: Incorporating Rixathon® for FL and DLBCL patients was associated with savings in acquisition costs and its coverage could be extended to more patients. Administration costs resulted in a marginal incremental cost that was offset by the biosimilar net savings.

Submitted: 5 December 2023; Revised: 19 February 2024; Accepted: 26 February 2024; Published online first: 4 March 2024

Introduction

Non-Hodgkin lymphoma (NHL) is the 11th most common cancer diagnosis and the 11th leading cause of cancer death in the world [1]. The frequency of NHL subtypes varies by region, with about 85% B-cell lymphomas and 15% T-cell lymphomas in western countries [2, 3]. Diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) are the most common non-Hodgkin lymphomas, accounting for 30% and 20% of all lymphomas reported in high-income countries, respectively [4, 5].

The treatment of these lymphomas will depend on the stage in which the patient is. The early stages usually do not require systemic therapy and, therefore, are treated by radiotherapy. Whereas, the advanced stages are treated with rituximab-based immunochemotherapy [6].

In Chile, treatment for both DLBCL and FL is covered by the public healthcare system through the Garantias Explicitas en Salud, GES mechanism (Regime of Explicit Health Guarantees). Patients can access immunochemotherapy such as rituximab-CHOP (cyclophosphamide, doxorubicin, vincristine and prednisone) and rituximab-COP (cyclophosphamide, vincristine and prednisone) [7]. In addition, patients eligible for high-cost oncologic drugs funding are treated with rituximab-bendamustine [8].

Rituximab is presented as an important treatment option in several guidelines both in cancer and rheumatology [9]. Despite this, the potential impact of biological therapies is often diminished in clinical practice because of inequalities in patient access, where budget constraints and cost-related barriers are key factors [9]. The approval of biosimilars of monoclonal antibodies represents a significant economic opportunity to health authorities worldwide as these molecules will generate price reduction and consequently will reduce the overall cost of biological therapy [10]. In Chile, rituximab biosimilars such as Rixathon® and Truxima® have entered in the Chilean market in 2019 [11].

Rixathon® is a biosimilar approved in Chile, the European Union and other highly regulated markets for use in all indications of reference rituximab [11, 12]. Since it represents therapeutic equivalence at a potential lower cost, there is a need to evaluate the budget impact associated with Rixathon® coverage in the Chilean health system. This study aimed to perform a budget impact analysis of the introduction of the intravenous biosimilar Rixathon® in patients with FL and large B-cell non-Hodgkin lymphoma (BCNHL) from the Chilean health system perspective.

Methods

Model structure
We developed a budget impact model in the Microsoft Excel platform to estimate cumulative costs and savings with the introduction of Rixathon® in the Chilean healthcare system. An expected cohort of DLBCL and FL patients were modelled. The budget impact analysis (BIA) was developed according to the recommendations proposed by the International Society for Pharmacoeconomics and Outcomes Research’s principles of good practice for BIAs [13].

In brief, an estimation of the eligible population was performed to calculate the expected cost attributable to DLBCL and FL management. For this cost estimate, two dimensions were considered: acquisition costs and administration costs. The BIA corresponds to the cost’s differences between the projected scenario (considering Rixathon®) and the actual scenario, see Figure 1.

Perspective and time horizon
The context of this analysis is the eventual incorporation of the biosimilar alternative Rixathon® for patients with DLBCL and FL, within the therapies available in the GES. Therefore, the analysis is done from the Chilean healthcare system’s perspective. The BIA was conducted over a 5-year time horizon (2023–2027).

Eligible population
For the eligible population estimation, a bottom-up approach was used based on rituximab units’ purchases by the Chilean public health system. This approach relies on the database that includes all tenders carried out at the public health system level that involve rituximab during the years 2015–2023. It should be noted that the tenders contained may or may not be mediated by Central de Abastecimiento del Sistema Nacional de Servicios de Salud, CENABAST (Central Supply of the National Health Services System), because there are tenders carried out directly by hospitals. This database that was obtained through formal public request, which is legally entitled by law, serve as the basis for estimating the number of individuals with both FL and DLBCL.

This approach estimates the number of individuals with FL and DLBCL based on the ratio between the milligrams of rituximab indicated annually for each pathology, and its expected dosage regimen [14]. Therefore, using the total amount of rituximab, adjustment factors – weighting multipliers systematically applied – were utilized which reflects the alternative use of rituximab in other pathologies. The bottom-up approach is presented in Figure 2.

For the public and private health system, the same distribution of the rituximab indication was assumed. Thus, the private rituximab amount was estimated by adjusting the milligram reported for the public health system with the relative weight of each subsystem: 17% private and 80% public [15]. In consequence, private rituximab milligrams correspond to 21% of those reported for the public health system. This estimation was done to calculate the number of milligrams marketed in the base year (2022). These estimates are presented in Appendix A.

To define the rituximab utilization between NHL and rheumatoid arthritis (RA), 7.5% of the total units was assumed to be used in other indications (renal disease, multiple sclerosis, off-label uses). This assumption is coherent with the judgement of experts, specifically physicians with more than 10 years of experience in oncology and academic background in this field. The information was gathered through a meeting and a survey with the selected experts in order to validate the model and its assumptions. They indicated that below 8% of rituximab proportion is used for other pathologies. It is important to highlight that this adjustment factor is applied only to the 100 mg and 500 mg presentation, since the 1,400 mg presentation its exclusively used for NHL [16].

Furthermore, all purchases made with funds from the high-cost drug scheme were used to estimate the units and milligrams indicated for RA [17]. This funding scheme is used exclusively to access rituximab treatment for RA. According to this database, 439,839 rituximab milligrams are allocated to RA, which represents 8.08% of the total mg registered for rituximab 500 mg (the formulation used for RA) [16].

Since no information regarding specific rituximab utilization for each pathology was available, it was assumed that rituximab shares will be distributed according to the relative proportions of each pathology among NHLs where rituximab is indicated. Therefore, T-cell NHLs were excluded, which represent about 15% of NHLs. Finally, the milligrams estimation for rituximab in the i-th pathology is detailed in Appendix B.

To report the individuals treated in subsequent years, a growth rate of 1.16%, which is assumed constant, was applied to the estimated population in the base year. This growth rate was obtained from the population projections reported by the National Institute of Statistics [18].

Comparators and market shares
Since our analysis will focus on determining the differences in costs that occur as a direct consequence of Rixathon® coverage, the other biosimilar alternative of rituximab, Truxima® was considered as a comparator. In addition, the innovator MabThera® SC (subcutaneous) and MabThera® IV (intravenous) administration formulations were also considered. In all projected scenarios, the increase in the inclusion of Rixathon® was attributed to the declining market share of MabThera®.

The market shares used for the current scenario were established based on the volume of purchases reported for each alternative with respect to the static total purchases for rituximab incurred during the year 2017 extended to 2023. The current scenario refers to the market partition currently present at the health system level, it does not consider an aggressive entry by the technology of interest (Rixathon®).

Regarding the projected scenario, three scenarios are proposed, in which the growth of Rixathon® will occur to the detriment of the innovative alternative of rituximab (MabThera®). In the first scenario, the growth of Rixathon® will occur at the expense of MabThera® IV, this scenario is the least conservative among those proposed since the coverage of Rixathon® will be associated only with savings in the treatment dimension (Rixathon® is cheaper and has administration costs equivalent to MabThera® IV). In the second scenario, the most conservative, Rixathon® will displace MabThera® SC, which will cause savings in treatments, but incremental costs in the administration dimension – SC administration is less expensive than IV administration. Finally, the third scenario to be evaluated corresponds to a combination of the first two scenarios, with Rixathon® replacing MabThera® IV and MabThera® SC – in a 50/50 ratio. The actual and projected scenarios are presented in Table 1.

Table 1

Given that the 500 mg MabThera® formulation is predominately used, the decrease in its market share due to the entry of Rixathon is thus more noticeable than that of MabThera® 100 mg.

Costs
Acquisition and administration costs were included as presented in Figure 1. Treatment costs were obtained directly from a database that contains tenders regarding rituximab purchases. Regarding the length of rituximab treatment and the potential for discontinuation, our assumption is that all patients successfully complete their therapy. An average cost was estimated between 2017–2023 for each comparator in this analysis, see Table 2. Regarding administration costs, we built baskets that contain the entire process required to administer rituximab. As a benchmark, we used the healthcare costing study of the Ministry of Health [19]. It should be noted that the administration time is not considered within this costing approach. This is because the Chilean tariffs are not expressed in function of the time spent per procedure. Finally, the costs are reported in USD as of July 2023 (1 USD = 813.4 Chilean Peso [CLP]).

Table 2

To determine the impact of differences in administration time, an additional approach was used. Here, time-driven activity-based costing (TDABC) was applied which estimates the expected cost of a given activity as the product between the cost of executing that activity per minute and the number of minutes used to perform that activity [20]. We used the estimates of employability and salaries reported by the Chilean Ministry of Education to value the hourly wage of a nursing professional [21]. Since no official source was found that reports the unit cost of an oncology administration chair per use or unit of time, the total daily cost of an ambulatory bed was used to conservatively reflect this expense. This approximation is in line with that reported by official costing exercises commissioned by the Chilean Ministry of Health [21].

Results

The main findings are presented in Table 3. The population is projected to increase from 1,274 individuals in the first year to 1,297 in year fifth, of which 41% represents patients with FL and 59% patients with DLBCL. In the scenario considering market share 1, Rixathon® increases at the expense of MabThera® IV. For 2023, we expect the health system has an estimated expenditure of US$9,504,101 while it would incur in an expenditure of US$9,295,548 to provide greater coverage to Rixathon®. This translates into a net saving of US$208,553 which is explained by the lower cost of the primary treatment. These savings would allow 49 additional patients to benefit from Rixathon®. Alternatively, this corresponds to a net saving of US$669,094 per 100 patients treated with Rixathon® (or US $6,691 per capita). The additional growth in savings during the following years further reflects the continued increase in Rixathon® market share.

Table 3

In the second scenario considering market share 2, Rixathon® increases at the expense of MabThera® SC. The health system incurs in the same Rixathon expenditure for year 1 as in scenario 1, i.e. US$9,295,208. This translates into a net savings of US$208,893, which is explained by a lower cost of drug acquisition combined with an increment in administration cost that is minimal (or US$4,096 per capita taking into account that 51 patients transition to the biosimilar in this scenario). In addition, the scenario 3 considers a Rixathon® expenditure of US$9,319,400 which results in net savings of US$185,701 in 2023 (or US$4,861 per capita given that 38 patients transition to the biosimilar).

Table 4 presents a breakdown of the net budget impact considering the TDABC administration cost approach. Here, the market share from the scenario 2 analysis was used (increased Rixathon market share in detriment of that of MabThera SC). This shows that for year 1 the expected costs are between US$9,636,579 to US$9,527,269, depending on the duration of the administration. Thus, nets savings are in the range of US$205,374 to US$199,314 for the first year followed by an increased growth in annual saving during the years thereafter that again reflects the increased market share of Rixathon.

Table 4

Discussion

This BIA was developed to estimate the costs in the Chilean healthcare system of the current and several projected scenarios where the market share of Rixathon® varies in the presence of intravenous and subcutaneous reference products over a 5-year time horizon. In particular, the present study considered the trade-off between differences in acquisition and administration costs for subcutaneous and intravenous formulations of rituximab.

Our population estimates were 528 and 744 individuals, for FL and DLBCL, respectively, on treatment with rituximab. The calculation was performed considering commercial rituximab records together with international evidence. This approach was deemed reasonable according to the consulted experts for estimating the number of effective individuals who received chemo-immunotherapy treatment during the 2023 period. In addition, this approach aligns with other budget impact analyses previously reported in the context of biosimilars [22, 23].

To our knowledge, this is the first budget impact in Latin-America that analyses the budget variations resulting from the inclusion of Rixathon® at the expense of the innovator rituximab. Several studies examining the overall budgetary impact of adopting biosimilars support our findings that the substitution of reference rituximab for its biosimilar results in costs savings [9, 23–26]. Additionally, the liberated budget could be used to purchase more Rixathon® and hence benefit more patients. Indeed, other studies in Europe have suggested that the introduction of biosimilars may extend treatment up to an additional 11% of patients in need of MabThera® treatment [9, 27]. Our findings show that in scenario 1 the net savings may extend the treatment for FL and DLBCL up to 2.4% (from 1,273 to 1,304 patients) in 2023, and 10.9% (from 1,297 to 1,456 patients) in 2027. This trend remains similar regardless of the scenario analysis. An important side note is that treatment extensions of course depends on the capacity of the health institution to deal with a larger number of intravenous infusions [23].

Since the same administration route was considered in scenario 1, no additional costs were associated with the inclusion of Rixathon®. Nevertheless, scenario 2 and 3 compared different administration route for rituximab (SC and IV) which results in incremental costs. However, those incremental costs represent between 3.8% and 2.2% of the total budget impact for scenario 2 and 3, respectively. Furthermore, the incremental cost is offset by savings in drug acquisition that allow an additional 43 to 250 new patients to receive Rixathon, respectively, for year 1 and 5 depending on the analysis scenario.

To assay the impact of treatment administration time more precisely, this study included TDABC method. The TDABC method presents an appealing approach due to its capacity to discern and quantify cost disparities stemming from the diverse routes of administration, specifically IV versus SC. These routes diverge in terms of the time expended by the administering healthcare professional, and the time allocated for the utilization of an administration chair. Notably, the scenario involving slow administration, aligning with extended administration times, exhibited diminished cost savings. Indeed, administration costs were twice as expensive as in scenario 2 (US$17,813 TDABC 240 min and US$8,234 scenario 2). This reduction in savings can be attributed to elevated incremental costs incurred in the administration process. Conversely, the scenario involving rapid infusion demonstrated the most substantial cost savings associated with the utilization of Rixathon®. This cost represents 5.41% of the total budget impact which implies an increase of 42% in the administration cost from scenario 2. Although there is a reduction in savings with the TDABC approach, this incremental cost is marginal. Certainly, the total net savings reflect between 92%–95% of the total budget impact, which may extend Rixathon® treatment to an additional 47 to 248 new patients between the first and fifth year, depending on the administration infusion time.

This study also faces some limitations. Price changes for existing therapies were neglected in the study. Prices of existing products might be lowered if competition increases with the entry of other products. It has been reported that the introduction of more competitors in tenders may increase price competition, leading to a potential reduction in tender prices [28, 29]. In Italy, the inclusion of an additional biosimilar competitor was associated with an average price reduction of approximately 10% [30]. Moreover, our research did not consider potential market access agreements, such as discounts on listed prices or alternative risk-sharing arrangements. Consequently, the current calculations of budgetary savings could potentially be inflated, while the projections of expenditure increases might be understated [31]. No vial sharing was considered in our estimation. However, this practice is variable and likely to differ between hospitals [31]. Also, the TDABC estimate did not account for the costs associated with ancillary services such as billing and human resources, because it is not feasible to account for every cost associated with healthcare delivery [32].

Furthermore, the estimates of the target population were obtained through the combination of multiple sources of information and assumptions supported by clinical experts. In this regard, the lack of empirical evidence could introduce some inaccuracy into our estimates. For instance, to inform the fraction of milligrams of rituximab to be used in other conditions (neither NHL nor RA), direct consultation with experts was conducted. Consequently, since we did not have data on rituximab purchases in the private healthcare sector, our model assumed that medication acquisition in the private healthcare system would follow a distribution equivalent to that reported in the public system. While this approach facilitated the estimation of the population with FL and DLBCL, it is essential to acknowledge that this assumption may not be entirely accurate in practice. Variations in the sociodemographic conditions of patients, along with other unaccounted factors, could influence the patterns of medication purchases recorded in the private sector.

Conclusion

This budget impact analysis emphasised that increased used of Rixathon® may result in considerable cost savings from a Chilean health system perspective. Several scenario analyses indicated that the incremental cost in terms of administration is marginal in relation to the net savings. Hence, the variation in administration costs should not be a barrier for the uptake of rituximab biosimilars. Additionally, the budgetary savings would be associated with an increase in patient accessibility to rituximab treatment. This evidence supports that biosimilars represent an interesting alternative to improve the efficiency and sustainability of the Chilean health system and contributes to the broader efforts to improve access to biosimilars in Latin America [33].

Funding sources

This study was funded by Sandoz Chile SpA.

Competing interests: The researchers declare that they have carried out this study within the framework of their salary conditions with the university and in no case have they received specific additional incentives for this study. Mr Tom’s Abbott has received fees from AbbVie and Boehringer Ingelheim for educational services and presentations. Mr Nicol’s Armijo has received fees from Roche and Sandoz for educational services and presentations. Dr Robin Piron is employed by the Sandoz Medical Department without any commercial incentives or other specific incentives for this study. Dr Manuel Espinoza has received fees from Merck, Grunenthal, Boehringer Ingelheim, Novartis, MSD, AbbVie, Roche, for training activities and presentations. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Tom’s Abbot ¹, MSc
Nicol’s Armijo ¹, MSc
Robin Piron ², PhD
Manuel Espinoza ^1,3, PhD

¹Health Technology Assessment Unit, Pontificia Universidad Católica de Chile
²Sandoz Chile
³Deparment of Public Health, Pontificia Universidad Católica de Chile

The data in Appendix A and B that support the findings of this study are available from the editorial office upon reasonable request.

References
1. Luo J, Craver A, Bahl K, Stepniak L, Moore K, King J, et al. Etiology of non-Hodgkin lymphoma: a review from epidemiologic studies. JNCC. 2022;2(4):226-34.
2. Perry AM, Diebold J, Nathwani BN, MacLennan KA, Müller-Hermelink HK, Bast M, et al. Non-Hodgkin lymphoma in the developing world: review of 4539 cases from the International Non-Hodgkin Lymphoma Classification Project. Haematologica. 2016;101(10):1244-50.
3. Polepole P, Mudenda VC, Munsaka SM, Zhang L. Spectrum of common Hodgkin lymphoma and non-Hodgkin lymphomas subtypes in Zambia: a 3-year records review. J Health Popul Nutr. 2021;40(1):37.
4. Singh R, Shaik S, Negi BS, Rajguru JP, Patil PB, Parihar AS, et al. Non-Hodgkin’s lymphoma: a review. J Family Med Prim Care. 2020;9(4):1834-40.
5. Thandra KC, Barsouk A, Saginala K, Padala SA, Barsouk A, Rawla P. Epidemiology of non-Hodgkin’s lymphoma. Med Sci (Basel). 2021;9(1):5.
6. Zelenetz AD, Advani RH, Buadi F, Cabanillas F, Caligiuri MA, Czuczman MS, et al. Non-Hodgkin’s lymphoma. Clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2006;4(3):258-310. Epub 2006/03/02. doi: 10.6004/jnccn.2006.0025. PubMed PMID: 16507273.
7. Ministerio de Salud de Chile. Listado específico de prestaciones. 17. Linfomas en personas de 15 años y más Santiago de Chile: Ministerio de Salud de Chile; 2022 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://auge.minsal.cl/problemasdesalud/lep/17
8. Ministerio de Salud de Chile. Drogas Oncológicas de Alto Costo (DAC) Santiago de Chile: Ministerio de Salud de Chile; 2022 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://www.minsal.cl/drogas-oncologicas-de-alto-costo-dac/
9. Gul’csi L, Brodszky V, Baji P, Rencz F, Péntek M. The rituximab biosimilar CT-P10 in rheumatology and cancer: a budget impact analysis in 28 European countries. Adv Ther. 2017;34(5):1128-44.
10. Almaaytah A. Budget impact analysis of switching to rituximab’s biosimilar in rheumatology and cancer in 13 countries within the Middle East and North Africa. Clinicoecon Outcomes Res. 2020;12:527-34.
11. Instituto de Saluda Pública. Sistema de Consulta de Productos Registrados Santiago de Chile: Instituto de Salud Pública; 2023 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://registrosanitario.ispch.gob.cl/
12. Smolen JS, Cohen SB, Tony H-P, Scheinberg M, Kivitz A, Balanescu A, et al. Efficacy and safety of Sandoz biosimilar rituximab for active rheumatoid arthritis: 52-week results from the randomized controlled ASSIST-RA trial. Rheumatology (Oxford). 2020;60(1):256-62.
13. Sullivan SD, Mauskopf JA, Augustovski F, Jaime Caro J, Lee KM, Minchin M, et al. Budget impact analysis—principles of good practice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value Health. 2014;17(1):5-14.
14. MINSAL. Problema de salud AUGE N°17. Linfoma No Hodgkin en personas de 15 años y más Ministerio de Salud de Chile: División de Prevención y Control de Enfermedades; 2023 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://diprece.minsal.cl/garantias-explicitas-en-salud-auge-o-ges/guias-de-practica-clinica/linfoma-en-personas-de-15-anos-y-mas/linfoma-no-hodgkin/documentos-relacionados/
15. Fondo Nacional de Salud. Datos abiertos Fonasa Santiago de Chile: Fondo Nacional de Salud; 2023 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://www.fonasa.cl/sites/fonasa/datos-abiertos/tablero-beneficiario
16. European Medicines Agency. Annex 1. Summary of product characteristics European Union: European Medicines Agency [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://www.ema.europa.eu/en/documents/product-information/mabthera-epar-product-information_en.pdf
17. CENABAST. Compras CENABAST Santiago de Chile: Central de Abastecimiento del Sistema Nacional de Servicios de Salud; 2023 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://www.cenabast.cl/compras-cenabast/
18. IHME. Global Burden of Disease: Results Tool. 2019 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: http://ghdx.healthdata.org/gbd-results-tool.
19. DESAL. Ministerio de Salud. Estudio verificación del costo esperado individual promedio por beneficiario del conjunto priorizado de problemas de salud con garantías explícitas 2021. Subsecretaria de Salud Pública. Departamento de Economía de la Salud: Ministerio de Salud de Chile, 2022 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: desal.minsal.cl/publicaciones/apoyo-reforma-ges/
20. Parikh NR, Chang EM, Kishan AU, Kaprealian TB, Steinberg ML, Raldow AC. Time-driven activity-based costing analysis of telemedicine services in radiation oncology. Int J Radiat Oncol Biol Phys. 2020;108(2):430-4.
21. Ministerio de Educación. Empleabilidad e ingresos Ministerio de Educación: Subsecretaría de Educación Superior; 2023 [homepage on the Internet]. [cited 2024 Feb 19]. Available from: https://educacionsuperior.mineduc.cl/empleabilidad-e-ingresos/
22. Boidart A, Darveau M, Déry N, Racine MC. Real-world budget impact of listing a biosimilar of rituximab. Can J Hosp Pharm. 2020;73(1):13-8.
23. Jang M, Simoens S, Kwon T. Budget impact analysis of the introduction of rituximab and trastuzumab intravenous biosimilars to EU-5 markets. BioDrugs. 2021;35(1):89-101.
24. Rognoni C, Bertolani A, Jommi C. Budget impact analysis of rituximab biosimilar in Italy from the hospital and payer perspectives. Glob Reg Health Technol Assess, 2018(5):228424031878428.
25. Calleja MA, Albanell J, Aranda E, García-Foncillas J, Feliu A, Rivera F, et al. Budget impact analysis of bevacizumab biosimilars for cancer treatment in adult patients in Spain. Eur J Hosp Pharm. 2023;30(e1):e40-e47.
26. García-Goñi M, Río-Álvarez I, Carcedo D, Villacampa A. Budget impact analysis of biosimilar products in Spain in the period 2009-2019. Pharmaceuticals (Basel). 2021;14(4):348.
27. Burcombe R, Chan S, Simcock R, Samanta K, Percival F, Barrett-Lee P. Subcutaneous trastuzumab (Herceptin®): a UK time and motion study in comparison with intravenous formulation for the treatment of patients with HER2-positive early breast cancer. Adv Breast Cancer Res. 2013;02(04):133-40.
28. Wouters OJ, Sandberg DM, Pillay A, Kanavos PG. The impact of pharmaceutical tendering on prices and market concentration in South Africa over a 14-year period. Soc Sci Med. 2019;220:362-70.
29. Renwick MJ, Smolina K, Gladstone EJ, Weymann D, Morgan SG. Postmarket policy considerations for biosimilar oncology drugs. Lancet Oncol. 2016;17(1):e31-e-38.
30. Curto S, Ghislandi S, van de Vooren K, Duranti S, Garattini L. Regional tenders on biosimilars in Italy: an empirical analysis of awarded prices. Health Policy. 2014;116(2):182-7.
31. Kanters TA, Stevanovic J, Huys I, Vulto AG, Simoens S. Adoption of biosimilar infliximab for rheumatoid arthritis, ankylosing spondylitis, and inflammatory bowel diseases in the EU5: a budget impact analysis using a Delphi panel. Front Pharmacol. 2017;8:322.
32. Wallace ZS, Harkness T, Blumenthal KG, Choi HK, Stone JH, Walensky RP. Increasing operational capacity and reducing costs of rituximab administration: a costing analysis. ACR Open Rheumatol. 2020;2(5):261-8.
33. Teran E, Gomez H, Hannois D, Lema M, Mantilla W, Rico-Restrepo M, et al. Streamlining breast cancer and colorectal cancer biosimilar regulations to improve treatment access in Latin America: an expert panel perspective. Lancet Oncol. 2022;23(7):e348-e358.

Author for correspondence: Nicolás Armijo, MSc, Health Technology Assessment Unit, Pontifi cia Universidad Católica de Chile, Diagonal Paraguay 362, Santiago, Chile

Disclosure of Conflict of Interest Statement is available upon request.

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Pharmacokinetic bioequivalence studies of a new Etoricoxib tablet formulation developed using proprietary MiST technology — risk assessment and mitigation using GastroPlus software

Posted on January 11, 2024

Author byline as per print journal: Dhananjay Panigrahi¹, MPharm; Aditya Murthy², MPharm, PhD; Shubham Jamdade², MPharm; Manoj Gundeti², MPharm; Nagarjun Rangaraj¹, MPharm, PhD; Anup Avijit Choudhury¹, MPharm; Tausif Ahmed², MPharm, PhD; Venkat Ramana Naidu¹, MPharm, PhD

Introduction: In this work, we present model` guided development of a new Etoricoxib tablet formulation using a proprietary technology. Application of absorption modelling using GastroPlus to guide the product development process is presented. An integrated approach of using in vitro, modelling and in vivo pharmacokinetics (PK) data to demonstrate bioequivalence between newly developed formulation and the commercial formulation is presented.
Methods: The MiST^TM technology is a combination of wetting-solubilizing agents with suspension-spray granulation technique. Physiologically-based biopharmaceutics model (PBBM) coupled with population PK and virtual bioequivalence were employed to guide the product development process. Commercially available GastroPlus 9.8 software was used for this purpose.
Results: Based on the simulation outcome, it was concluded that the new cost-effective formulation manufactured using MiST^TM technology could be bioequivalent against the marketed formulation. This was further confirmed from the in vivo PK studies in normal healthy volunteers.
Conclusion: The simulated data were in line with the observed PK data obtained from the in-house bioequivalence study. This work demonstrates application of predictive modelling and simulation tools to accelerate new product development.

Submitted: 26 May 2023; Revised: 9 November 2023; Accepted: 15 November 2023; Published online first: 28 November 2023

Introduction

Developing new drug products is a resource intensive process. The model-informed drug development (MiDD) is an approach where biological, mathematical, and statistical models are applied to the drug development process to save time and cost of development [1]. On a broader level, this approach has three fundamental pillars: (1) Understanding of pharmacokinetics (PK) and pharmacodynamics (PD) of the drug; (2) Developing mathematical models that integrate data from PK, PD (preclinical and clinical studies) and in vitro studies; and (3) Applying the knowledge from the models to make decisions at various stages of development [1]. This is applicable to development of both innovator and generic drug products. It can accelerate development and help in effective regulatory decision-making [2].

The objectives of this work are presented below

Develop a new, cost-effective tablet formulation for Etoricoxib with a proprietary MiST technology; further, the new formulation must have improved dissolution rate and must be bioequivalent to a commercially available reference product with early onset of action in fed state.
Utilize existing (literature), in-house PK data and in vitro dissolution data to develop a physiologically based biopharmaceutics model (absorption model) using GastroPlus®.
Validate the model with available data and employ the model for population PK and virtual bioequivalence (VBE) predictions that can aid in making informed decisions during product development.

Etoricoxib (ETR) is an orally active [5-chloro-2-(6-methylpyridin-3-yl)-3-(4-methylsulfonylphenyl) pyridine] derivative, see Figure 1, that selectively inhibits the cyclooxygenase-2 (COX-2) [3]. It belongs to the selective COX-2 inhibitors of the class non-steroidal anti-inflammatory drugs (NSAIDS) [4]. Compared to the other COX-2 inhibitors like rofecoxib, valdecoxib and celecoxib, ETR displays a higher COX-1 to COX-2 binding ratio (IC50 of 1.1 ± 0.1 μM for COX-2 and 116 ± 8 μM for COX-1) [5]. Thus, ETR is highly selective towards the COX-2 and has superior gastrointestinal safety and tolerability compared to other drugs in the same therapeutic class. The ETR has become drug of choice in the treatment of acute pain, acute gouty arthritis, chronic low back pain, primary dysmenorrhea, and chronic treatment for the signs and symptoms of osteoarthritis and rheumatoid arthritis [6].

The ETR is a weakly basic drug (pKa 4.6) and classified as BCS class II. It demonstrates pH dependent solubility (soluble in acidic media) [7]. It is soluble in at pH <1.2, but insoluble at pH >3. Gastrointestinal transit of ETR from gastric to intestinal region results in precipitation of the drug [8]. Hence, its oral absorption displays high fast-fed variability. Administration after a high-fat meal results in a 36% reduction of the maximum concentration (C_max) and increase in maximum time (T_max) by 2 h (T_max in fasting state 1h, under fed it is 3h) [9]. Increase in T_max under fed state results in delayed absorption of the drug, thus delaying onset of action [10]. Significant differences in the exposure are observed between fasting and fed states.

The primary objective of this work was to develop a new, cost-effective formulation of ETR and to evaluate its in vivo performance using in vitro (dissolution) and in silico (absorption modelling) tools. In the past, many research groups have explored approaches to develop more effective ETR by various approaches like amorphous solid dispersion [11], complexation with -cyclodextrin [6] and co-solvency approach [12]. Additionally, nanoparticulate formulations like niosomes and solid lipid nanoparticles have also been evaluated [13] and [14]. However, none of them have demonstrated the scalability of the proposed technologies. In the current work, we have developed a proprietary formulation technology (MiST^TM) that is a combination of homogenization and top spray granulation approaches. This technology is easily scalable and can be readily translated to commercial product. This work details the application of proprietary MiST^TM technology to develop ETR tablets and subsequent in vitro and in silico evaluation.

Materials and methods

Materials

Etoricoxib was procured from in-house source, Polymeric stabilizer was obtained from Dow Chemicals, India. Wetting agent was obtained from BASF, India. Lactose monohydrate was procured from DFE Pharma, India; microcrystalline cellulose (MCC) was procured from FMC Bio, India. Aerosol 200 was obtained from Evonik, India.

Methods

Formulation development
Quality by design approach (QbD)
The QbD is a systematic approach that enables researchers to develop a formulation with in-built quality attributes. Unlike the traditional approaches where the quality is tested after the product is developed, in the QbD approach, quality is built into the product. Development of a product using QbD approach involves utilizing prior knowledge, design of experiments (DoE) risk and knowledge management. Product development via QbD pathway involves establishing quality target product profile (QTPP), identifying critical quality attributes (CQAs), critical material attributes (CMAs), critical process parameters (CPPs) all of which can be bundled as critical bioavailability attributes (CBAs) [15].

Homogenization and manufacture of spray dispersion
The drug, stabilizer, wetting agent and disintegrant were dispersed in water. This dispersion was homogenized using high shear homogenizer (Ultraturrax T-25, IKA, Germany). The homogenization time was optimized based on the particle size of the dispersion obtained [16].

Particle size analysis
Particle size analysis by dynamic light scattering
The homogenized dispersion (before top spray granulation) was subjected to particle size analysis using Zetasizer Nano ZS (Malvern Instrument Ltd., Worcestershire, UK). The dispersion was diluted ~10X with Milli-Q water and analysed for particle size [15].

Top spray granulation
The core material (lactose monohydrate and microcrystalline cellulose) were loaded into top spray bowl and the drug dispersion was top sprayed onto the core material. Granulation was continued using fluid bed processor (GPCG 1.1, Glatt, Germany) using parameters presented in Table 1. The granules were blended, lubricated and compressed into spherical-shaped tablets.

Table 1

In vitro drug release evaluation
The objective of this work was to develop a novel test formulation using novel MiST Technology that can be administered under fed conditions. The new product had to be bioequivalent with the reference ETR tablets under fed conditions. Hence, dissolution studies were performed in the media that mimic human fed physiology. Dissolution studies were performed with N = 6 units in the following media considering fed relevant conditions:

a) 10 mM acetate buffer, pH 4.5 ± 0.1
b) 10 mM acetate buffer, pH 5.5 ± 0.1

Absorption modelling and simulation using GastroPlus®

GastroPlus® version 9.8 (Simulations Plus Inc, USA) was employed to build a physiologically-based biopharmaceutical model (PBBM) for ETR tablets 120 mg. The population PK model was utilized to predict drug plasma concentrations using dissolution inputs from physiologically relevant media under fed conditions. The stepwise approach followed to build the model for ETR tablets is presented in Figure 1.

Physicochemical and biopharmaceutical properties of Etoricoxib
The physicochemical and biopharmaceutical properties of ETR were defined using a combination of literature-based inputs and optimized inputs from the simulations. In case of unavailability of literature parameters, ADMET predicted parameters from GastroPlus® were considered. ETR is a BCS Class II compound, and it exhibits pH dependent solubility – low solubility in alkaline pH and highly soluble in the acidic pH [7]. Solubility profile of ETR across physiological pH range is presented in Figure 2.

Pharmacokinetics of Etoricoxib
Orally administered ETR is well absorbed. The absolute bioavailability is approximately 100%. Peak plasma concentration under fasting is 1 h; under high fat meal it is 2 h [17]. ETR is extensively metabolized with <1% of a dose recovered in urine as the parent drug. The principal metabolite is the 6’-carboxylic acid derivative of ETR. It is approximately 92% bound to human plasma protein over the range of concentrations of 0.05 to 5 μg/mL. The volume of distribution at steady state (V_dss) was approximately 120 L in humans. Following administration of a single 25-mg radiolabelled intravenous dose of ETR to healthy subjects, 70% of radioactivity was recovered in urine and 20% in feces, mostly as metabolites. Less than 2% was recovered as unchanged drug. Dosing with food (a high-fat meal) had no effect on the extent of absorption of ETR after administration of a 120-mg dose. The rate of absorption was affected, resulting in a 36% decrease in C_max and an increase in T_max by 2 hours. These data are not considered clinically significant. The PK of ETR is linear across the clinical dose range (30 mg–120 mg) [18].

Model development and verification
The ACAT model was developed using following inputs: (1) PK profile of oral solution formulation product from the literature [19]; (2) solubility data across physiological pH range was generated from literature and used as an input in the model [17]; (3) disposition PK calculated from oral solution profile. Two compartment model was fitted as best fit model; and (4) Model was verified with literature reported data [16].

The verified model was then employed to assess VBE between the new test formulation against the reference product. For this, dissolution data for the respective formulation were used as inputs. The verified model was employed to predict VBE between novel MiST formulation against the reference product.

Results

Formulation development

In the MiST^TM technology, drug is homogenized with addition of wetting agent. This process has dual benefits: (1) increase in the surface area of the API due to homogenization; and (2) improved wetting of the API due to use of surfactant during the process. Particle-size reduction was achieved by homogenization of the dispersion using high speed homogenizer. The initial particle size of the API was 16 ± 4 μm, which was further micronized to 3.3 ± 3 μm using the homogenization process. The polymeric stabilizer used to stabilize the drug suspension also helps in preventing Ostwald ripening [18].

Characterization of Etoricoxib tablets

In vitro evaluation
In our current study, BE study evaluation was performed under fed condition. Therefore, for dissolution comparison, fed state relevant dissolution media were employed. Comparative dissolution profiling was performed between novel ETR formulation and few commercial formulations in the following buffers: pH 4.5 acetate buffer, pH 5.5 acetate buffer, FeSSIF v2 (pH 5.8) and pH 5.5 acetate buffer with 0.2 M sodium chloride. Results of the dissolution studies are illustrated in Figure 3. As seen from the figure, the novel ETR formulation with MiST technology demonstrated significantly faster dissolution profile in all the tested media compared to other commercial products. ETR in the commercial product (reference) demonstrated pH dependent solubility; however, the novel ETR product manufactured with proprietary technology mitigated the pH dependent behaviour. This formulation enablement is particularly useful for molecules that demonstrate significant pH and food effect. Mitigating the same with enabled formulation is beneficial in improving both patient convenience and compliance.

Dissolution data used for the simulations

Dissolution data indicated significant improvement in dissolution for the new test product when compared to marketed formulations of Product A and Product-B (reference products) in all the fed relevant media, i.e. pH 4.5 Acetate Buffer, pH 5.5 Acetate Buffer with or without 0.2M NaCl and FeSSIF v2 media. However, for the modelling purpose, considering the T_max, absorption region of the drug and fed physiology, dissolution in pH 4.5 Acetate Buffer media, pH 5.5 Acetate Buffer media were used with Z-factor fitting in GastroPlus®.

Model development and verification
Human PK parameters were estimated by fitting 100 mg oral solution data to a two-compartment model using PKPlus^TM module [19]. The best-fit compartment model was selected. The parameters used as input in the model are presented in Table 2.

Table 2

Virtual BE study simulations were performed by using input in vitro dissolution data. The simulation outcomes are presented in Table 3 and Figure 4. Based on this initial risk assessment, the test formulation was selected for PK-BE studies. Equation 1 was used for calculating PE%.

PE% = ((Predicted value-Observed value)/
(Observed value)) × 100 – Equation 1

Acceptance criteria: ± 15% for individual PK parameters and ± 10% for mean PK parameters

Table 3

Virtual BE simulations from GastroPlus®
Simulation studies were performed using developed and verified model under fed physiology. The modelling outcomes are presented in the Supplementary Material. The results are tabulated in Table 4.

Table 4

Model refinement using in-house study data
Based on the in-house data obtained from the PK-BE study, the earlier model (developed from literature data) was further optimized to accurately predict the absolute values of PK parameters. The observed vs predicted outcome from the refined model is presented in Table 5.

Table 5

Figure 5 demonstrates observed and simulated PK profile for the commercial formulation (Product A) 120 mg tablets.

The results demonstrate that the observed PK parameters for the reference product (Product A) from in-house study was close to the simulated PK parameters predicted parameters. PE of less than 10% for both C_max and AUC was obtained.

Utilizing this refined and more accurate model, population simulations using demographic data from the BE study were performed for both reference and new test product. VBE simulation was performed to validate the model with respect to actual BE results and 90% confidence interval for both C_max and AUC was computed. The simulated VBE outcome was computed against obtained BE outcome. This comparison is presented in Table 6.

Table 6

From Table 6, it is evident that the optimized model was well predictive of the obtained BE results. Further, both pH 4.5 Acetate Buffer and pH 5.5 Acetate Buffer media were indicative of the in vivo performance of ETR absorption. The IVIVR between in vitro dissolution studies in these media and the in vivo absorption is presented in Figure 6.

An IVIVR between in vitro dissolution and in vivo fraction absorbed indicates that, both the dissolution media (Acetate Buffer pH4.5 & pH5.5) were well-predictive of in vivo absorption for ETR.

Based on in vitro in vivo relationship for the commercial (reference) Product-A, these media can be considered bio reflective for ETR tablets under fed conditions. The ETR demonstrates low solubility across pH 4.5 to 7.0; however, the ADMET predicted permeability is high (5.23 x 10^-5 cm/sec). It is absorbed rapidly and extensively from the upper part of the small intestine, reaching maximum serum concentrations within few hours after oral administration. Oral bioavailability of ETR from tablet dosage form is ~90–100%. Hence, dissolution in pH conditions relevant to upper GIT are more critical for predicting the in vivo performance of this product.

Discussion

As ETR is reported to be a BCS class II with pH dependent solubility, the prime objective of this study was to reduce the pH dependency on dissolution. It was hypothesized that reduction of pH dependent solubility behaviour could reduce the fasting vs fed variability seen with this drug. A proprietary MiST technology was employed in the manufacture of novel ETR tablets. The novel formulation had faster dissolution in fed relevant dissolution media compared with the marketed formulation. This enhanced drug release from the developed formulation could be explained by enhanced improved solubility of the API across pH conditions. Particle size reduction and addition of a wetting agent along with process parameters could contribute to enhanced drug dissolution in the novel product. Particle size reduction would create new surfaces and also increases the effective surface area for a poorly wetting drug like ETR [20]. As per Ostwald-Freundlich equation, decrease in the radius causes an increase in the surface area to volume ratio leading to enhanced solubility [19]. Incorporation of wetting agent (surfactant) is important to enhance the solubility of poorly soluble drugs. These surfactants are amphiphilic molecules with both hydrophilic and hydrophobic regions. Enhancement of ETR solubility by incorporation of SLS has been reported earlier [6].

The homogenized drug dispersion is uniformly top sprayed onto the core material. Hence, this approach yielded granules with good dissolution [6]. This uniform coating of drug around the core material would also lead to increased surface area and better solubility.

Dissolution testing is employed to assess the impact of formulation and manufacturing variables on the performance of the drug product. In case of novel ETR formulation, the rate of dissolution was faster compared with the conventional commercial formulations. Advances in PBBM and simulation help in integrating in vitro dissolution data with physiological factors to predict in vivo performance of the drug product [21]. In some of the earlier work from our group, we have demonstrated various applications of PBBM to predict in vivo performance of the drug product. In a publication by Swati et al., virtual BE was utilized to understand the effect of dissolution specification changes on the drug product performance [22]. In another recent article, we have demonstrated utilization of PBBM to understand the impact of faster dissolution profile on the in vivo performance of the drug product [23]. Numerous articles on the application of PBBM to understand the impact of dissolution on the product performance have been published. Farhan et al., have demonstrated the use of PBPK model to accelerate product development and improve the success of BE for generic products [24]. In another recent publication on Vildagliptin MR product, utilization of PBBM to propose clinically relevant dissolution specifications has been demonstrated [25]. However, despite the advances in PBPK modelling for predicting in vivo performance of new drug products, there are some known limitations. For example, Wu et al. report the concept of finite absorption time in PBPK modelling. It is known that, in vivo, the drug absorption terminates after a specific point of time. Nevertheless, in the current commercially available software, the models assume continued absorption across the GIT, often leading to over-predicted plasma drug concentrations [26].

In the present study, we have demonstrated utilization of PBBM in predicting the in vivo performance of the novel ETR drug product. We have utilized PBBM as a bridge to connect in vitro dissolution with in vivo performance. From this study, it has been demonstrated that the novel formulation manufactured by proprietary MiST technology showed faster dissolution profile, independent of the media pH conditions. It also demonstrated BE with the reference product. The simulations also demonstrated that the novel formulation could achieve bioequivalence compared to conventional commercial formulations without compromising on the extent of absorption. An IVIVR was also established to demonstrate the relevance of dissolution in pH 4.5 & pH 5.5 AB to predict the in vivo performance of the drug product.

Conclusion

In this work, we have presented a novel enablement approach that could be used to mitigate pH effect, especially for BCS II drugs. Further, through appropriate dissolution data inputs in the model, we have demonstrated that the novel drug product can be bioequivalent to commercial formulation (reference product). This work provides an integrated approach of using an enabled formulation, in vitro and in silico tools to overcome the limitations of ETR formulation. This approach can be extended to other BCS II drugs and has potential to accelerate the drug development process, thus reaching patients faster. In this work, an integrated MiDD approach was utilized to assess the in vivo performance risk for the new test product and to accelerate product development. Although we have presented a simple case here, the same approach could be effectively utilized for the aiding the development of more complex drug products in the future.

Acknowledgements

The authors would like to thank Dr Reddy’s Laboratories Ltd for providing an opportunity to publish this work.

DRL Publication Number: PUB00628-23.

Funding sources

This work was funded by Dr Reddy’s Laboratories Ltd. No other funding was received for this work.

Author contributions

DP, AM, AAC, TA and VRN are involved in concept and design, writing manuscript and manuscript review. SJ, NR, MG are involved in concept and design and writing manuscript.

Disclaimer

The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Compliance with ethical standards

The study protocol was approved by MAARG independent Ethics committee with meeting No: MIEC-052-21 & Informed consent was confirmed by the ethics committee.

Competing interests: All the authors (DP, AM, SJ, MG, NR, AAC, TA and VRN) are employees of Dr Reddy’s Laboratories Ltd and declare that they have no conflict of interest. The authors alone are responsible for the content and writing of this article.

Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Dhananjay Panigrahi¹, MPharm
Aditya Murthy², MPharm, PhD
Shubham Jamdade², MPharm
Manoj Gundeti², MPharm
Nagarjun Rangaraj¹, MPharm, PhD
Anup Avijit Choudhury¹, MPharm
Tausif Ahmed², MPharm, PhD
Venkat Ramana Naidu¹, MPharm, PhD

¹BRaIN-Formulation R&D-DF, Dr Reddy’s Laboratories Ltd, Hyderabad, India
²Global Clinical Management, Dr Reddy’s Laboratories Ltd, Hyderabad, India

References
1. Madabushi R, Seo P, Zhao L, Tegenge M, Zhu H. Role of model-informed drug development approaches in the lifecycle of drug development and regulatory decision-making. Pharm Res. 2022;39(8):1669-80.
2. Bi Y, Liu J, Li L, Yu J, Bhattaram A, Bewernitz M, et al. Role of model-informed drug development in pediatric drug development, regulatory evaluation, and labeling. J Clin Pharmacol. 2019;59:S104-S111.
3. Riendeau D, Percival MD, Brideau C, Charleson S, Dube D, Ethier D, et al. Etoricoxib (MK-0663): preclinical profile and comparison with other agents that selectively inhibit cyclooxygenase-2. J Pharmacol Exp Ther. 2001;296(2):558-66.
4. Matsumoto AK, Cavanaugh Jr, PF. Etoricoxib. Drugs Today (Barc). 2004;40(5):395-414.
5. Cochrane DJ, Jarvis B, Keating GM. Etoricoxib. Drugs. 2002;62(18):2637-51.
6. Babu S. A factorial study to evaluate the individual and combined effects of [beta]-cyclodextrin and tween 80 on the solubility and dissolution rate of aceclofenac. Asian J Chem. 2010;22(6):4281.
7. Mitra A, Kesisoglou F, Dogterom P. Application of absorption modeling to predict bioequivalence outcome of two batches of etoricoxib tablets. AAPS PharmSciTech. 2015;16(1):76-84.
8. Gonzalez-Alvarez I, Bermejo M, Tsume Y, Ruiz-Picazo A, Gonzalez-Alvarez M, Hens B, et al. An in vivo predictive dissolution methodology (IPD methodology) with a BCS class IIb drug can predict the in vivo bioequivalence results: Etoricoxib products. Pharmaceutics. 2021;13(4):507.
9. Agrawal NG, Porras AG, Matthews CZ, Rose MJ, Woolf EJ, Musser BJ, et al. Single-and multiple-dose pharmacokinetics of etoricoxib, a selective inhibitor of cyclooxygenase-2, in man. J Clin Pharmacol. 2003;43(3):268-76.
10. Sapkal SB, Adhao VS, Thenge RR, Ashok R, Darakhe SAS, Shrikhande VN. Formulation and characterization of etoricoxib solid dispersion using natural polymers. Turk J Pharm. 2020;17(1):7-19.
11. Dani P, Puri V, Bansal AK. Solubility advantage from amorphous etoricoxib solid dispersions. Drug Dev Ind Pharm. 2014;40(1):92-101.
12. Nayak AK, Panigrahi PP. Solubility enhancement of Etoricoxib by cosolvency approach. International Scholarly Research Notices. 2012.
13. Kesharwani R, Sachan A, Singh S, Patel D. Formulation and evaluation of solid lipid nanoparticle (SLN) based topical gel of etoricoxib. J Appl Pharm Sci. 2016;6(10):124-31.
14. Ravalika V, Sailaja AK. Formulation and evaluation of etoricoxib niosomes by thin film hydration technique and ether injection method. Nano Biomed Eng. 2017;9(3):242-8.
15. Rangaraj N, Reddy Pailla S, Chowta P, Sampathi S. Fabrication of ibrutinib nanosuspension by quality by design approach: intended for enhanced oral bioavailability and diminished fast fed variability. AAPS PharmSciTech. 2019:20(8):326.
16. Alizadeh MN, Shayanfar A, Jouyban A. Solubilization of drugs using sodium lauryl sulfate: experimental data and modeling. J Mol Liq. 2018;268:410-14.
17. European Medicines Agency. Arcoxia [homepage on the Internet]. [cited 2023 Nov 9]. Available from: https://www.ema.europa.eu/en/documents/referral/arcoxia-article-6-12-referral-annex-i-ii-iii-iv_en.pdf
18. Müller RH, Peters K. Nanosuspensions for the formulation of poorly soluble drugs: I. Preparation by a size-reduction technique. Int J Pharmaceutics. 1998;160(2):229-37.
19. Rodrigues AD, Halpin RA, Geer LA, Cui D, Woolf EJ, Matthews CZ. Absorption, metabolism, and excretion of etoricoxib, a potent and selective cyclooxygenase-2 inhibitor, in healthy male volunteers. Drug Metab Dispos. 2003;31(2):224-32.
20. Saleh, Mubarak Abdullah, Salam A. Mohammed, Ezzat C. Abdullah, and Laith A. Hashim. Enhancement the dissolution rate and solubility of poorly soluble drugs. In Advanced Materials Research. Vol. 701, pp. 234-238. Trans Tech Publications Ltd, 2013.
21. Wu D, Li M. Current state and challenges of physiologically based biopharmaceutics modeling (PBBM) in oral drug product development. Pharm Res. 2023;40(2):321-36.
22. Jaiswal S, Ahmed T, Kollipara S, Bhargava M, Chachad S. Development, validation and application of physiologically based biopharmaceutics model to justify the change in dissolution specifications for DRL ABC extended release tablets. Drug Dev Ind Pharm. 2021;47(5):778-9.
23. Aishwarya R, Murthy A, Ahmed T, Chachad S. A novel approach to justify dissolution differences in an extended release drug product using physiologically based biopharmaceutics

Author for correspondence: Tausif Ahmed, MPharm, PhD, Head Biopharmaceutics and Bioanalytical, Global Clinical Management, Dr Reddy&rquo;s Laboratories Ltd, IPDO, Bachupally Campus, Qutbullapur Mandal, Hyderabad – 500090, Telangana, India

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 08/11/2024

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Canadian prescribers’ attitudes and perceptions about ophthalmic biosimilars

Posted on May 4, 2023

Author byline as per print journal: Michael S Reilly, Esq; Jane Barratt, PhD

Introduction: The first biosimilar entered the Canadian market in 2009 and the first ophthalmic biosimilar was approved in 2022. In 2022, the Alliance for Safe Biologic Medicines (ASBM) and the International Federation on Ageing (IFA) asked prescribing ophthalmology physicians in Canada for their views on product identification, prescribing biologicals and prescribing biosimilars and switching.
Methods: In October/November 2022, the ASBM conducted a web-based quantitative survey with 41 participants practicing ophthalmology in Canada. Prescribers were asked for their views on several aspects: how products are identified; the influence of the cost of biologicals and biosimilars on prescribing; prescribing biosimilars and switching to biosimilars; pharmacist-level switching to biosimilars, and automatic substitution of biosimilars.
Results: The survey reveals information about biological product identification and shows that the ophthalmologists are confident in the Canadian pharmacovigilance system’s ability to accurately identify the specific product that might be responsible for an adverse drug reaction. Most physicians are not influenced by the cost when prescribing biologicals and they are confident prescribing biosimilars and switching patients to biosimilars where appropriate. Overall, 90% of practitioners think they should have the sole authority to decide what biological is dispensed to patients and over 80% are not comfortable with third-party switching for non-medical reasons. The majority of practitioners said that the system that would best serve the patients of their province would be one in which multiple products, including innovator and biosimilars, are reimbursed, biosimilars are encouraged for new patients, and there is no automatic substitution.
Conclusion: The survey reveals information about how Canadian ophthalmologists feel about the use of ophthalmic biosimilars, specifically on biological/biosimilar product identification, and prescribing and switching to biosimilars for ocular use.

Submitted: 24 February 2023; Revised: 25 April 2023; Accepted: 26 April 2023; Published online first: 9 May 2023

Introduction

In Canada, the first biosimilar product approved by Health Canada entered the market in 2009, this was Sandoz’s growth hormone treatment Omnitrope (somatropin) [1, 2]. By June 2022, 50 biosimilar products had been approved in Canada [2, 3]. This includes the first ophthalmology biosimilar, Byooviz (SB11), approved in 2022 and produced by Samsung Bioepis and commercialized by Biogen which is a biosimilar of Genentech (Roche)/Novartis’ blockbuster eye drug Lucentis (ranibizumab) [4].

India paved the way for ophthalmology biosimilars, with the first ophthalmic biosimilar of ranibizumab approved in 2015 (Razumab, Intas Pharmaceuticals Ltd, Ahmedabad, Gujarat, India) [5, 6]. Following expiry of the originator patents in regions across the world, Byooviz has been the first ophthalmology biosimilar to be approved in regions such as Europe, the US and Canada [7, 8].

The introduction of anti-vascular endothelium-derived growth factors (anti-VEGF), such as ranibizumab, for the treatment of various retinal vascular diseases has transformed ophthalmology. Now that biosimilars of these drug products are available or are in the pipeline, they have the potential to impact more patients worldwide by offering more affordable treatment options [6].

Ranibizumab inhibits angiogenesis (the formation of new blood vessels) by inhibiting VEGF-A. Ranibizumab can be used to treat macular degeneration by inhibiting VEGF, which is responsible for the excessive formation of blood vessels in the retina leading to progressive loss of vision. The monoclonal antibody drug is indicated for the treatment of wet age-related macular degeneration (AMD), macular oedema, degenerative myopia and diabetes complications; all conditions of the eye causing vision loss [9].

The use of compounded bevacizumab in ophthalmology is widespread globally [6, 10]. However, the application of this biological is off-label as, for example in the US, the product is FDA-approved to treat colorectal cancer, and it has not been through the rigorous FDA process required for approval to treat ophthalmic pathology [11]. Compounded ziv-aflibercept is also used off-label despite intravitreal use being contraindicated in the EU because of its hyperosmotic properties [12]. The compounding of these products for use in retinal diseases may also increase the risk of intraocular infections [13–16]. Although biosimilars of these products have been approved or are in the pipeline, the US American Academy of Ophthalmology (AAO) advises against the use of biosimilars of these products in ophthalmology as they have not been studied for ophthalmic indications and their inactive ingredients have not all been approved for use in the eye [17, 18].

A survey carried out by the International Retina Biosimilar Study Group (Inter BIOS Group) revealed that many retinal physicians from Europe and the US have concerns regarding the safety and efficacy of biosimilars [19]. Due to the off-label use of biologicals in this field, the concern may be well founded. However, biosimilar products of biologicals that are approved for ocular treatment should not pose a problem as regulators have very robust tests to determine biosimilarity that allow any clinically meaningful differences between originators and potential biosimilars to be determined, and this is also true for anti-VEGF biosimilars, such as ranibizumab [10]. In January 2022, the AAO issued a policy statement on the biosimilars in ophthalmologic use [17]. The guideline outlines that, for an ophthalmic biosimilar, a comparative clinical trial is generally required in addition to a similarity comparison, and this includes extensive pharmacokinetic and pharmacodynamic analysis with phase III equivalence studies where appropriate [11]. The acceptance and use of biosimilars is key in the field of ophthalmology as they can reduce the cost of care for debilitating eye diseases and increase access to treatment globally.

Many provinces of Canada have adopted a switching policy wherein patients are switched from expensive originator products to lower-cost approved biosimilar versions of the drug. Such policy decisions are made in a bid to drive down healthcare costs and increase access to treatment however they have been met with some opposition [20]. Such switching policies may influence the opinion of ophthalmology practitioners in Canada regarding biosimilars.

In 2022, the Alliance for Safe Biologic Medicines (ASBM) commissioned a web-based survey to be conducted by ophthalmology practitioners/physicians across Canada. This was designed to document ophthalmologist perspectives on: identification of biologicals/biosimilars (by brand name, non-proprietary name or DIN) and the reporting of adverse drug events related to them; the cost of biologicals and biosimilars and how this may influence if they are prescribed; prescribing biosimilars and switching to biosimilars; pharmacist-level switching to biosimilars and automatic substitution of biosimilars.

This survey was very similar to those previously carried out in Australia [21], Europe [22, 23], South America [24] and the US [25–27) that asked for prescriber opinions on prescribing practices, naming and labelling of biologicals, switching and substitution and the interchangeability designation.

Sample characteristics and methodology

In October/November 2022 the ASBM conducted a web-based survey of 41 ophthalmology practitioners in Canada.

Low sample size was a function of finding not just ophthalmologists, but those who are retinal specialists in Canada (those who prescribe biologicals). These are a new specialty in which biosimilars are becoming available; results are consistent with other ASBM physicians’ surveys conducted in Australia, Canada, Europe, Latin America and the US using identical methodology and questions.

Survey respondents are from Industry Standard Research’s (ISR) contracted partner’s commercially available physician panel that covers more than 70 countries worldwide. They receive between US$25 and US$75 for survey participation, depending on specialty and geography.

The physician panel provider uses their internal database of more than 1,000,000 healthcare professionals worldwide for sampling. Also, when necessary, the physician panel provider partners with other market research companies to meet the demands of healthcare clients in the industry. The market research companies go through very selective vetting processes as well as training on ISO certification and market research industry standards to make sure all provide the best service to clients.

ISR’s physician panel provider uses the following channels for recruitment:

Professional conferences
Direct Mail
Online recruitment
Email, fax, mailing lists of verified market research companies.

All survey respondents are managed online through the market research companies’ patented, internal, proprietary system, which is ISO 26362 certified since 2011.

The questionnaires were developed as a collaboration between ASBM and IFA management and membership, and ISR management. No ‘validation’ has been conducted as the instruments do not measure higher level ‘constructs’. They are purely direct measures of opinion and attitude.

Details of respondent profile

The participants worked in a number of different practice types, including: the community setting, academic medical practice, private family practice, multi-specialty clinics and hospitals. They came from the provinces of: Ontario, Quebec, British Colombia (BC), Alberta, New Brunswick and Manitoba. With the majority (54%) coming from Ontario, and just under a quarter (24%) from Quebec, see Figure 1.

All participants (100%) said they prescribe biologicals. Regarding the knowledge of biosimilars, the vast majority of participants (95%) said they were either very familiar, with a complete understanding of them, or familiar with a basic understanding, however 2% did say they had never heard of biosimilars, see Figure 2.

With regards to tenure in medical practice, most participants (44%) have been practicing for between 11–20 years, whilst 27% have been practicing for under 11 years and 29% have been practicing for over 20 years.

Online survey

Prescribers were asked to consider:

When identifying a prescription of a biological drug in patient records, are they likely to identify the medicine by their product/brand name or their non-proprietary/generic name.
In the context of identifying a biological for purposes of reporting an adverse event, are they likely to identify the medicine by their product/brand name, non-proprietary/generic name or DIN number.
Confidence levels in the Canadian pharmacovigilance system’s ability to accurately identify the specific product, at the brand-name level, that might be responsible for an adverse drug reaction.
How often they include the lot/batch number when recording adverse drug reactions.
The reasons for not including the lot/batch number when recording adverse drug reactions (relevant to prescribers who rarely or never include the lot/batch number only).
If they would support Health Canada harmonizing internationally by adopting a distinct suffix system.
How costs to the public system impact which biological drug they prescribe.
If cost to the public system were not a factor, how would that impact their choice of originator biological vs biosimilar prescription (relevant only to those who were impacted by the cost of biologicals to the public system).
Their comfort levels: a) prescribing a biosimilar to a ‘treatment-naïve’ patient; and b) switching a stable patient from one medicine to a biosimilar.
How they are influenced by the quality of a biological’s patient support program.
The importance of patient education on biosimilars prior to switching a patient to a biosimilar.
The importance of having the authority to designate a biological medicine as ‘DISPENSE AS WRITTEN’ or ‘DO NOT SUBSTITUTE’, when: a) faced with a situation where substitution by a pharmacist; or b) faced with a situation where it is permissible for payer (public or private) to require a patient who is stable on their current biological to switch to a biosimilar.
The importance of a) being notified by the pharmacist that a patient has received a biological other than the one prescribed, if the patient was receiving chronic (repeated) treatment; and b) having the sole authority to decide, together with patients, the most suitable biological medicine for their disease.
How acceptable it would be if the pharmacist made the determination which biological (originator or biosimilar) to dispense to a patient on initiation of treatment.
Their comfort levels: a) when switching patients to a biosimilar for non-medical reasons, i.e. coverage; or b) with a third-party switching of a patient to a biosimilar for non-medical reasons, i.e. coverage.
If a patient’s treatment gains were risked by switching to a biosimilar, would they be supportive of a patient’s right to choose the appropriate treatment for their individual circumstance?
Their main concern about non-medical switching to a biosimilar.
The importance of a) government tenders for biosimilars to be awarded to multiple suppliers; and b) factors besides price to be taken into account in national tender offers.
Whether scenario a or b would be better for patients: a) is when multiple products, including innovator and biosimilars are reimbursed, and biosimilars may be encouraged for new patients with no automatic substitution permitted; and b) is when only government chosen biosimilars are reimbursed and new patients must be prescribed this and current patients forced to switch.

All data refer only to those who completed the survey. All data were analysed in MS Excel and checked manually.

Results

Identification and naming of biological products during use and reporting of adverse drug events

When carrying out the survey, participants were first given two explanatory texts to examine. These were given immediately preceding Question 7 (and 8):

Biological medicines are therapeutic proteins produced using living cells. The active substances of biological medicines are larger and more complex than those of non-biological medicines. A biosimilar medicine is a biological medicine that is developed to be similar to an existing biological medicine (the ‘reference product’). Biosimilars are not the same as generics, which have simpler chemical structures and are considered to be identical to their reference medicines.
In Canada biologicals and biosimilars are approved nationally by Health Canada under the New Drug Submission pathway. As a result of patent expiry on the originator products, biosimilars are increasingly becoming available in Canada. Unique to Canada, the patient support program (PSP) for a biological is paid for by the manufacturer and a change in biological medications means a change in PSP if the manufacturer is different.

The question considered whether or not prescribers identify biological or biosimilar products by their product/brand name or their non-proprietary /generic name, 80% said they used the brand name and 20% the non-proprietary. Regarding the reporting of adverse events, 78 % said they use the product/brand name, 20% use the non-proprietary name, and 2% use the Drug Identification Number (DIN) number.

When asked to consider how confident they were in the Canadian pharmacovigilance system’s ability to accurately identify the specific product, at the brand-name level, that might be responsible for an adverse drug reaction, 39% of participants were highly confident, 56% somewhat confident and 5% not confident.

When asked whether they include the lot/batch number when recording adverse drug reactions, 39% of respondents said they always did this, 34% said they usually did, and 27% said this was done sometimes, rarely or never. Of the (11) respondents who said they sometimes, rarely or never recorded the lot/batch number, 64% said this was because they did not have it available at the time of reporting, 9% said the system/form does not have a dedicated field for this, 9% said they forget to include this information and 18% had other reasons, which include, that they have not yet had to report adverse drug reactions, see Figure 3.

Again, participants were first given two explanatory texts to examine. These were given immediately preceding Question 12.

In 2015, the World Health Organization’s International Nonproprietary Names (INN) Programme proposed that a distinguishing suffix be appended to all biological medicines, including biosimilars, that share an INN to clearly differentiate them from each other and improve global pharmacovigilance. Health Canada was an early supporter of this proposal; and has indicated it would harmonize with the World Health Organization (WHO) if this system were made available.
Health Canada has also held talks about harmonizing nomenclature with the US, which uses a suffix system similar to that proposed by WHO. Health Canada currently relies on self-reporting of brand name and DIN to differentiate similar products from one another.

Then, when asked if they would support Health Canada harmonizing internationally by adopting a distinct suffix system, the majority said they would support this (88%).

Prescribing biologicals: cost, switching, patient support programs and patient education
When asked about the cost of prescribing biologicals, 63% of respondents said they prescribe the biological drug they think is most appropriate regardless of cost, and 37% said they make an evaluation of the biological drug benefits and cost to the public system when prescribing. If cost was not a factor, of the (15) respondents who make an evaluation based on the cost of the product, 40% said they would decide between the innovator and biosimilar based on the individual situation, whereas 40% would prescribe the innovator, with 20% tending to prescribe the biosimilar, see Figure 4.

When asked about comfort levels when prescribing a biosimilar to a treatment naïve patient, 83% said they were very or somewhat comfortable and 17% were somewhat or very uncomfortable with this. When asked about switching a stable patient to a biosimilar, 62% said they were very or somewhat comfortable and 39% were somewhat or very uncomfortable with this, see Figure 5.

When asked if the quality of a biological’s PSP has an influence on which biological is prescribed, 53% of respondents said it has a moderate or significant influence and 46% of respondents said it had minimal or no influence, see Figure 6.

When asked about the importance of patient education on biosimilars prior to switching a patient to a biosimilar, 44% of respondents said it is critical or very important, 42% said it was somewhat important and 14% said it was slightly important or not important.

Prescribing biosimilars and substitution

Again, participants were first given two explanatory texts to examine. These were given immediately preceding Question 19 .

Health Canada has stated, biosimilars are not ‘generic biologicals’ … authorization of a biosimilar is not a declaration of pharmaceutical equivalence, bioequivalence or clinical equivalence to the reference biological drug. Health Canada Biosimilar Guidance Document, November 2019.
In Canada, the term ‘interchangeability’ often refers to the ability for a patient to be changed from one drug to another equivalent drug, by a pharmacist, without the intervention of the prescriber who wrote the prescription. The authority to declare two products interchangeable rests with each province/territory according to its own rules and regulations.

When faced with a situation where substitution by a pharmacist is an option in their province, 88% of practitioners thought it was critically or very important for them to have the authority to designate a biological medicine as ‘DISPENSE AS WRITTEN’ or ‘DO NOT SUBSTITUTE’, see Figure 7.

When faced with a situation where it is permissible for a payer (public or private) to require a patient who is stable on their current biological to switch to a biosimilar, 91% of practitioners thought it was critically or very important to have the authority to designate a biological medicine as ‘DISPENSE AS WRITTEN’ or ‘DO NOT SUBSTITUTE’, see Figure 7.

The majority (61%) thought it was not acceptable for a pharmacist to determine which biological (innovator or biosimilar) to dispense to a patient on initiation of treatment and the decision should be made by the practitioner. The minority (39%) thought it was either totally acceptable or acceptable, if agreed in advance, for a pharmacist to determine which biological (innovator or biosimilar) to dispense to a patient on initiation of treatment, see Figure 8.

The majority (90%) of practitioners stated that it was critically or very important for them to have the sole authority to decide, together with patients, the most suitable biological medicine for their disease.

Regarding personally switching patients to a biosimilar for non-medical reasons, i.e. cost or coverage, 66% of practitioners were very or somewhat comfortable with this idea, see Figure 9. Concerning third-party switching of a patient to a biosimilar for non-medical reasons, i.e. cost or coverage, 81% of practitioners stated they were not comfortable with this idea.

The majority (76%) said that if patient’s treatment gains were risked by switching to a biosimilar, they would be supportive of a patient’s right to choose the appropriate treatment for their individual circumstance.

When asked about their main concerns about non-medical switching to biosimilars, the top concerns were potential symptom return in patients (20%), legal liability as a physician (13%), unknown immunogenicity reactions (10%) and potential adverse effects of biosimilars (8%). However, the remaining 50% of practitioners responded ‘All of the above’ which also included, change in patient support system, potential psychological impacts, and potential impact of adherence, see Figure 10.

When asked about the importance of government tenders for biosimilars to be awarded to multiple suppliers, 66% said it was very or somewhat important. Regarding how important it is for factors besides price to be taken into account in national tender offers, e.g. reliability of supply, patient support services, manufacturer reputation, 91% said it was critical, very or somewhat important, see Figure 11.

Again, participants were first given two explanatory texts to examine. These were given immediately preceding Question 30.

In nearly every Western European country, physicians are encouraged to prescribe lower-cost biosimilars to new patients, but ultimately retain the authority to choose between multiple products when prescribing – all of which will to be reimbursed by the payer. Automatic or forced substitution is strongly discouraged and cost savings are achieved through competition between multiple reimbursed products.
In contrast, some Canadian provinces are adopting the approach used in Eastern Europe: all patients, both treatment-naïve and those who are stable on their current biological, will be switched to the preferred, government-chosen biosimilar in order to achieve cost savings.

Following this, the majority (78%) said that the system that would best serve the patients of their province would be one in which multiple products, including innovator and biosimilars, are reimbursed, biosimilars are encouraged for new patients and there is no automatic substitution. However, 15% said that they supported a system where only government-chosen biosimilars are reimbursed, new patients must be prescribed to this product and current patients are forced to switch.

Conclusion

The survey demonstrates information about Canadian ophthalmology physicians’ thoughts on the use of biosimilars for ocular use. Specifically, it reveals information about how these physicians record and identify biological/biosimilar drug products (product identification) and shows that the ophthalmologists are confident in the Canadian pharmacovigilance system’s ability to accurately identify the specific product, at the brand-name level, that might be responsible for an adverse drug reaction. It also highlights that, regarding prescribing biologic al s, most physicians are not influenced by the cost when prescribing biologicals and they are confident prescribing biosimilars and switching patients to biosimilars where appropriate. They also hold patient education and support programmes in high regard. Overall, physicians believe that, regarding switching (by pharmacists or payers), it is important that physicians have the authority to designate a biological medicine as ‘DISPENSE AS WRITTEN’ or ‘DO NOT SUBSTITUTE’ and they want to be informed when pharmacists dispense biologicals that differ to those prescribed. Overall, 90% of practitioners think they should have the sole authority to decide what biological is dispensed to patients and over 80% are not comfortable with third-party switching for non-medical reasons. The majority of practitioners said that the system that would best serve the patients of their province would be one in which multiple products, including innovator and biosimilars, are reimbursed, biosimilars are encouraged for new patients and there is no automatic substitution.

Funding sources

The survey study was funded by the Alliance for Safe Biologic Medicines (ASBM) and administered by Industry Standard Research, LLC.

The ASBM is an organization composed of diverse healthcare groups and individuals – from patients to physicians, innovative medical biotechnology companies and others – who are working together to ensure patient safety is at the forefront of the biosimilars policy discussion.

The activities of the ASBM are funded by its member partners who contribute to ASBM’s activities. Visit www.SafeBiologics.org for more information.

Authors

Michael S Reilly, Esq
Executive Director, Alliance for Safe Biologic Medicines, PO Box 3691, Arlington, VA 22203, USA

Jane Barratt, PhD
Secretary General, International Federation on Ageing, Suite G.238, 1 Bridgepoint Drive, Toronto, Ontario, M4M 2B5, Canada

Competing interests: Mr Michael S Reilly, Esq is the Executive Director and employed by Alliance for Safe Biologic Medicines. Mr Reilly served in the US Department of Health and Human Services from 2002 to 2008.

Dr Jane Barratt is the Secretary General, International Federation on Ageing and has no conflicts of interest. Unrestricted grants and sponsorship have been received in the field of vision health for more than a decade.

Provenance and peer review: Not commissioned; externally peer reviewed.

References
1. GaBI Online – Generics and Biosimilars Initiative. Trends in biological drugs in Canada [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/reports/Trends-in-biological-drugs-in-Canada
2. GaBI Online – Generics and Biosimilars Initiative. Biosimilars approved in Canada [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/biosimilars/general/biosimilars-approved-in-canada
3. GaBI Online – Generics and Biosimilars Initiative. Canada approves five biosimilars in last seven months [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/biosimilars/news/canada-approves-five-biosimilars-in-last-seven-months
4. GaBI Online – Generics and Biosimilars Initiative. Canada approves ranibizumab biosimilar Byooviz [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/biosimilars/news/canada-approves-ranibizumab-biosimilar-byooviz
5. GaBI Online – Generics and Biosimilars Initiative. ‘Similar biologics’ approved and marketed in India [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/biosimilars/general/Similar-biologics-approved-and-marketed-in-India
6. Sharma A, Kuppermann BD, Loewenstein A. The future of biosimilars and biobetters in ophthalmology. touchREVIEWS in Ophthalmology. 2022;16(1):6–7.
7. Biogen. FDA Approves Samsung Bioepis and Biogen’s BYOOVIZTM (SB11), LUCENTIS® Biosimilar (ranibizumab-nuna) [homepage on the Internet]. [cited 2023 Apr 25]. Available from: https://investors.biogen.com/news-releases/news- release-details/fda-approves-samsung-bioepis-and-biogens-byooviztm-sb11
8. Ranibizumab biosimilar (Byooviz) gains EU marketing authorization. Am J Manag Care. 2021 Aug 30. https://www.centerforbiosimilars.com/view/samsung-bioepis-byooviz-gains-ema-marketing-authorization.
9. GaBI Online – Generics and Biosimilars Initiative. Biosimilars of ranibizumab [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/biosimilars/general/Biosimilars-of-ranibizumab
10. Sharma A, Parachuri N, Kumar N, Bandello F, Kuppermann BD. Biosimilar anti-VEGF-yardsticks to ensure biosimilarity. Eye. 2023;37(4-5).
11. Hariprasad SM, Gale RP, Weng CY, Ebbers HC, Rezk MF, Tadayoni R. An Introduction to biosimilars for the treatment of retinal diseases: a narrative review. Ophthalmol Ther. 2022;11(3):959-82.
12. European Medicines Agency. Zaltrap summary of product characteristics. 2017 [homepage on the Internet]. [cited 2023 Apr 25]. Available from: https://www.ema.europa.eu/en/documents/product-information/zaltrap-epar-product-information_en.pdf
13. Daien V, Nguyen V, Essex RW, Morlet N, Barthelmes D, Gillies MC; Fight Retinal Blindness! Study Group . Incidence and outcomes of infectious and noninfectious endophthalmitis after intravitreal injections for age-related macular degeneration. Ophthalmology. 2018;125(1):66-74.
14. Goldberg RA, Flynn HW Jr, Isom RF, Miller D, Gonzalez S. An outbreak of streptococcus endophthalmitis after intravitreal injection of bevacizumab. Am J Ophthalmol. 2012;153(2):204-8.e1.
15. Ricci F, Calabrese A, De Felici C, Missiroli F, Pileri M, Regine F. A cluster of presumed, noninfectious endophthalmitis after intravitreal injection of bevacizumab: long-term follow-up. Digit J Ophthalmol. 2016;22(2):41-5.
16. VanderBeek BL, Bonaffini SG, Ma L. Association of compounded bevacizumab with postinjection endophthalmitis. JAMA Ophthalmol. 2015;133(10):1159-64.
17. American Academy of Ophthalmology. Position Statement. Use of biosimilars in ophthalmic practice. 2022 Jan [homepage on the Internet]. [cited 2023 Apr 25]. Available from: https://www.aao.org/clinical-statement/use-of-biosimilars-in-ophthalmic-practice
18. GaBI Online – Generics and Biosimilars Initiative. American Academy of Ophthalmology biosimilars position statement published [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/biosimilars/general/american-academy-of-ophthalmology-biosimilars-position-statement-published
19. Sharma A, Holz FG, Regillo CD, Freund KB, Sarraf D, Khanani AM, et al; International Retina Biosimilar Study Group (Inter BIOS Group). Biosimilars for retinal diseases: United States – Europe awareness survey (BIO-User – survey). Expert Opin Biol Ther. 2023:1-9. doi:10.1080/14712598.2023.2176218
20. GaBI Online – Generics and Biosimilars Initiative. Concerns over Canada’s New Brunswick transition to biosimilars [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2023 Apr 25]. Available from: www.gabionline.net/biosimilars/general/concerns-over-canada-s-new-brunswick-transition-to-biosimilars
21. A survey of Australian prescribers’ views on the naming and substitution of biologicals. Generics and Biosimilars Initiative Journal (GaBI Journal). 2017;6(3):107-13. doi: 10.5639/gabij.2017.0603.022
22. Dolinar RO, Reilly MS. Biosimilars naming, label transparency and authority of choice – survey findings among European physicians. Generics and Biosimilars Initiative Journal (GaBI Journal). 2014;3(2):58-62. doi: 10.5639/gabij.2014.0302.018
23. Feldman MA, Reilly MS. European prescribers’ attitudes and beliefs on biologicals prescribing and automatic substitution. Generics and Biosimilars Initiative Journal (GaBI Journal). 2020;9(3):116-24. doi:10.5639/gabij.2020.0903.020
24. Reilly MS, Gewanter HL. Prescribing practices for biosimilars: questionnaire survey findings from physicians in Argentina, Brazil, Colombia and Mexico. Generics and Biosimilars Initiative Journal (GaBI Journal). 2015;4(4):161-6. doi: 10.5639/gabij.2015.0404.036
25. Gewanter HL, Reilly MS. Naming and labelling of biologicals – a survey of US physicians’ perspectives. Generics and Biosimilars Initiative Journal (GaBI Journal). 2017;6(1):7-12. doi: 10.5639/gabij.2017.0601.003
26. Schneider PJ, Reilly MS. Naming and labelling of biologicals – the perspective of hospital and retail pharmacists. Generics and Biosimilars Initiative Journal (GaBI Journal). 2016;5(4):151-5. doi:10.5639/gabij.2016.0504.040
27. McKibbin RD, Reilly MS. US prescribers’ attitudes and perceptions about biosimilars. Generics and Biosimilars Initiative Journal (GaBI Journal). 2022;11(3):96-103. doi:10.5639/gabij.2022.1103.016

Author for correspondence: Michael S Reilly, Esq, Executive Director, Alliance for Safe Biologic Medicines, PO Box 3691, Arlington, VA 22203, USA

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 29/07/2024

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Pharmacokinetics and relative bioavailability of sitagliptin hydrochloride and sitagliptin phosphate tablets formulations: a randomized, open-label, crossover study in healthy male volunteers

Posted on January 5, 2023

Author byline as per print journal: Chuei Wuei Leong¹, PhD; Elton Sagim¹, BBiomedSc, Kar Ming Yee¹, BPharm; Muhammad Shalhadi Saharuddin¹, BSc; Sharifah Radziah Syed Abd Rahim¹, MSc; Khairil Sabri¹, BSc; Mohd Zulhairi Jamaluddin¹, BSc; Shahnun Ahmad¹, MBBS; Atiqah Amran¹, BSc; Rabab F Tayyem², PhD

Introduction/Study Objectives: The present study aimed to evaluate the comparative bioavailability of a new generic sitagliptin formulation.
Methods: This was an open label, randomized, balanced, two-sequence, two-treatment, two-period, single oral dose, crossover, bioequivalence (BE) study in 30 healthy male volunteers under fasting conditions. A 100 mg single dose of sitagliptin in the form of sitagliptin hydrochloride monohydrate (test) and sitagliptin phosphate monohydrate (reference) tablets were administered to each volunteer, separated by one week washout period. Twenty-two blood samples were collected at pre-dose and up until 48 hours post-dose. Sitagliptin concentrations were determined via a validated LC-MS/MS method following a protein precipitation step. Pharmacokinetic (PK) parameters were estimated via non-compartmental analysis and then compared between the reference and test formulations by performing a multivariate analysis of variance.
Results and Discussion: No statistically significant difference was found between the test and reference formulations in terms of the maximum concentration (C_max), area under the curve (AUC), AUC_0-inf, and AUC_0-48. The 90% confidence intervals of sitagliptin Ln-transformed C_max, AUC_0-inf, and AUC_0-48 were within the regulatory BE acceptance range of 80%–125%.
Conclusion: The test formulation met regulatory definition of BE to the reference formulation under fasting condition in these healthy male volunteers.

Submitted: 15 September 2022; Revised: 29 November 2022;Accepted: 30 November 2022; Published online first: 20 December 2022

Introduction/Study Objectives

Diabetes mellitus is a highly prevalent disease affecting over half a billion people, accounting for over 10% of the world’s adult population, with an anticipated 46% increase by 2045 and a drastic economic and health burden [1]. Most diabetic patients present with type 2 diabetes mellitus (T2DM) [2], characterized by impaired insulin sensitivity resulting in hyperglycaemia [3]. Furthermore, T2DM is associated with both microvascular and macrovascular complications that are the major causes of its morbidity and mortality [4, 5]. As T2DM progresses, pancreatic β cells progressively deteriorate, requiring effective glycaemic control that can be achieved by lifestyle modifications and treatment with any of a number of hypoglycaemic agents [3].

Sitagliptin is an oral hypoglycaemic agent that selectively inhibits the dipeptidyl peptidase-4 (DPP-4) enzyme [6] responsible for the inactivation of the glucagon-like peptide-1 (GLP-1) and the glucose-dependent insulinotropic polypeptide (DPP-4). DPP-4 inhibition results in an incremental prolongation of incretin activity leading to a glucose-dependent boost of insulin secretion and a decrease in glucagon secretion [7]. Sitagliptin’s glycaemic control effect is characterized by lowering of both fasting and postprandial glucose concentrations [8]. DDP-4 inhibitors (DPP-4i) are well tolerated when given either alone or in combination with other hypoglycaemic agents and its use is associated with a clinically insignificant risk of hypoglycaemia or weight gain [9]

The absorption of sitagliptin is rapid, with a median time to the maximum concentration (T_max) of 1–4 hours and an apparent half-life (T_1/2) of 8–14 hours [10, 11]. Sitagliptin is metabolized via oxidation catalyzed mainly by cytochrome P450 (CYP) 3A4 isoenzymes in the liver, with a small contribution from CYP2C8 [12]. Sitagliptin area under the curve (AUC) is increased in a relatively dose-dependent fashion in healthy volunteers [11] and its absolute bioavailability was found to be 87%. The majority of a sitagliptin dose is excreted unchanged in urine (87%) and feces (13%) [12, 13]. The renal elimination of sitagliptin is by active tubular secretion. Its renal clearance has been reported to be 388 mL/min [11]. Therefore, renal function is expected to be a significant factor affecting the pharmacokinetics (PK) of sitagliptin [14]. However, no dose adjustment is required in patients with only mild renal impairment; that is patients with a creatinine clearance of equal to or more than 50 mL/min but less than 80 mL/min. Minor decreases in renal function were found to have a clinically insignificant impact on sitagliptin PK. [14].

Different sitagliptin salts, e.g. hydrochloride, malate, and tartrate, have judged to have similar bioavailabilities compare to the reference sitagliptin phosphate product (Januvia^®) with similar safety and efficacy profiles when they were given market authorization [15]. In a recent study comparing the tablet formulations of sitagliptin hydrochloride with sitagliptin phosphate, the uniformity of dosage form as measured by weight variability was found to be superior in sitagliptin hydrochloride tablets. Furthermore, sitagliptin hydrochloride tablets were shown to have superior chemical stability compared to sitagliptin phosphate and were therefore considered a better option [16]. Similar dissolution profiles were also demonstrated for both sitagliptin phosphate and hydrochloride salts, with an acceptable similarity factor, indicating that both salts have similar in vivo behaviour [17]. This was explained by sitagliptin’s high bioavailability and solubility [18]. This study aimed to evaluate the relative bioavailability of a test formulation (containing 100 mg of sitagliptin in the form of sitagliptin hydrochloride) with a reference tablet formulation (containing 100 mg of sitagliptin in the form of sitagliptin phosphate).

Methods

Study design

The relative bioavailability of a single dose of a test formulation with a reference formulation, both containing 100 mg sitagliptin, was evaluated in an open-label, randomized, balanced, two-period, two-way, two-sequence crossover study design in healthy, fasting adult volunteers. The washout period was one week between the two study periods.

The study was carried out in the ACDIMA BioCentre in Amman, Jordan in accordance with the International Conference on Harmonization–Good Clinical Practice, the Declaration of Helsinki, and the ASEAN (Association of Southeast Asian Nations) guideline for the conduct of bioequivalence (BE) studies. Approval was obtained from the ACDIMA BioCenter’s Institutional Review Board (IRB) (Research ID: 940-2019) on 15 September 2020 and the Jordan Food and Drug Administration (JFDA) (Research ID: 6/BIO/20) on 5 February 2020. Informed consents were obtained from all participants prior to enrolment. The study was also registered in the Thai Clinical Trials Registry (TCTR20220628001) on 28 June 2022.

Study population

Participants were recruited based on the fulfilment of the inclusion criteria of: 1) healthy as confirmed by the medical evaluation [basic medical check-up, medical history, electrocardiogram (ECG), and laboratory findings (complete blood count, biochemical tests, serological tests, and urine analysis] performed on admission; 2) body mass index (BMI) of 18.5 to 30 kg/m² (weight more than 59 kg); 3) adults aged between 18 and 50 years; 4) not receiving any medications for the last two weeks prior to the commencement of the study; 5) non-pregnant women; 6) with fasting blood glucose concentration of more than 70 mg/dL prior to dosing at the start of each period. Exclusion criteria included: 1) heavy smokers (more than 10 cigarettes per day); 2) presence of any contraindications or allergies to sitagliptin; 3) consumption of grapefruits products in the prior week or caffeinated beverages within two days of the study date; and 4) abuse of alcohol or illicit drugs which was confirmed by laboratory testing (alcohol saliva test and urine test for benzodiazepines, amphetamine, marijuana, cocaine and opiates).

Based on sample-size calculation to achieve a power of 80%, considering an intra-subject and inter-subject coefficient of variation (ISCV) for sitagliptin AUC following a 100 mg single dose found in the literature to be around 5.8% and 15.1%, respectively [19], a minimum of 12 subjects was required to be recruited; therefore, thirty subjects from the Jordan population were enrolled for this study.

Study products and administration

The BE of Fortreas^® tablets (containing 100 mg of sitagliptin in the form of sitagliptin hydrochloride) manufactured by Duopharma, Malaysia (test formulation) was compared with Januvia^® tablets (containing 100 mg of sitagliptin in the form of sitagliptin phosphate) manufactured by Merck Sharp & Dohme Ltd, England (reference formulation) in the present study. Volunteers were assigned randomly to ingest the reference or test tablet with 240 ± 2 mL of water after overnight fasting of 10–12 hours. Subjects were instructed to stay in an upright position for four hours after dosing. Standardized meals were served to all volunteers at a fixed schedule throughout the study where on Day 1, standardized dinner (chicken scallop sandwich) was served 12 hours before dosing and on Day 2, standardized lunch (chicken rice and bread) was served 4 hours after dosing, a snack 8 hours after dosing, and a standardized dinner (chicken scallop sandwich) 12 hours after dosing. Fluid restrictions were placed only on Day 2 of the study. Subjects were not allowed to drink water 1 hour before dosing and 4 hours after, except for: 120 ± 2 mL of water was served 1 hour before dosing, 240 ± 2 mL of water with the dose and 120 ± 2 mL of water 2 and 3 hours after dosing.

Sampling

A total of 22 blood samples (7 mL each) were taken from each volunteer at pre-dose and 0.3, 0.7, 1, 1.3, 1.7, 2, 2.3, 2.7, 3, 3.3, 3.7, 4, 4.3, 4.7, 5, 6, 8, 10, 12, 23, and 48 hours post-dose. Lithium heparin tubes were used for blood samples collection; then, centrifugation at 4,000 RPM for 5 min at 10°C was carried out. Plasma was separated and stored in the freezer (-70°C), then transferred to the bioanalytical laboratory site of the on-site ACDIMA BioCentre–Bioanalytical Unit and stored in a freezer (-70°C) until the bioanalytical analyses were performed.

Subject monitoring

Throughout the study, clinical assessments and laboratory investigations were performed in an attempt to evaluate both protect the safety of all participants and report and assess any adverse events observed during the study.

Determination of sitagliptin plasma concentrations

An analytical method for the estimation of sitagliptin in human plasma was developed and validated using reversed-phase liquid chromatography and tandem mass spectrometry (LC-MS/MS) with positive ion electrospray ionization (Agilent, USA). Plasma was extracted through protein precipitation where 200 μL of each plasma sample was spiked with 25 μL Sitagliptin D4 as an internal standard; then 1 mL of the precipitation solvent, acetonitrile, was added, and the mixture was vortexed and centrifuged for 5 min at 6,000 RPM at 5°C. Afterward, 10 μL was injected via the autosampler, and separation was performed using an Agilent Eclipse XDB CN (150 × 4.6 mm, i.d.: 5 μm) at 35°C and a flow rate of 1 mL/min of the mobile phase, which was composed of acetonitrile and 50 mM ammonium formate (50:50, v/v) with 0.5 mL formic acid. Quantitation of the analyte was done on a triple-stage quadrable mass spectrometer. Sitagliptin and internal standard were monitored at the molecular ion 408.2–412.1 m/z and MS/MS (daughter) 235.0–239.0 m/z, respectively. Validation of the method was carried out in the range of concentrations between 1 ng/mL to 750 ng/mL with good linearity of r² equals 0.999. The method achieved intra-and inter-day precision of less than 5% and accuracy of 98.8%–103.5%. The analyte and the internal standard recoveries were 82%–88%. The limit of quantification was found to be 1 ng/mL. Between-and within-day CV% were below 3.3% and 4.5%, respectively.

Pharmacokinetic and statistical analysis

The randomization schedule was carried out using SAS software. The data analysts were blinded for the randomization, and the bioanalytical laboratory conducting the PK analysis was blinded for the identity of the test and reference product ingested to avoid any bias arising from the open-label study design. Pharmacokinetic parameters were estimated by performing non-compartmental PK analysis using the Phoenix WinNonlin version 8.1 (Pharsight Corporation, USA) in terms of maximum concentration (C_max), AUC, 0 to infinity (AUC_0–inf), AUC, 0 to 48 hours (AUC_0–48), elimination constant (K_e), T_max, and T_1/2 of the drug. Statistical analysis was carried out using SAS software version 9.4 (SAS Institute Inc, Cary, North Carolina) by performing multivariate analysis of variance (ANOVA) on the Ln-transformed and untransformed PK parameters C_max, AUC_0–48, and AUC_0–inf using the linear mixed effects model with sequence and period X treatment were included as the fixed effects and subjects as the random effect. The test formulation BE with the reference product was established based on an alpha value of 0.05 (within a 90% confidence interval (CI)).

Results and discussion

The relative bioavialability of a test formulation with a reference formulation in 30 healthy male volunteers under fasting conditions was investigated in the current study in an attempt to meet regulatory requirements for declaring the test formulation to be bioequivalent to the reference product. The participation of four volunteers was terminated due to the violation of the study protocol during the second period (positive results of illicit drugs). One volunteer withdrew during the second period due to personal reasons. While women meeting the inclusion and exclusion criteria were eligible to be enrolled, only male volunteers were successfully recruited. Data obtained from 25 male volunteers who completed the study were included in the analysis with a mean ± standard deviation BMI of 25.0 ± 2.7 kg/m² and age of 27.6 ± 9.5 years, as summarized in Table 1. Mild headache was reported in one subject, while the white blood cells count (WBC) was above the normal range for two (13.5 and 15.3 × 10⁹ cells/L) for two participants 48 hours after the dose. However, these changes were not considered to be clinically significant.

Table 1

A one week washout period, sufficient to cover at least ten elimination half-lives of sitagliptin, was included in the crossover study design between the two phases to avoid any possible carryover phenomenon. The PK parameters of the reference and test formulations, i.e. AUC_0-inf, AUC_0-48, C_max, T_max, and T_1/2, are presented in Table 2. C_max, AUC_0-inf, and AUC_0-48 values were comparable between the test and reference formulations. Furthermore, intrasubject variabilities in C_max were found to be 20.3% and 23.6%, AUC_0-48, 14.3% and 15.6%, and AUC_0-inf, 14.4% and 15.4% for the test and reference formulation, respectively. Tmax achieved comparable results with those reported in previous BE studies of a single dose of sitagliptin 100 mg [20] or 50 mg [21] tablet in American Hispanic/Latino and non-Hispanic/Latino volunteers. All PK parameters were identical to those recently reported in a Malaysian population following a 100 mg single dose of sitagliptin tablet [22]. C_max, T_max, and T_1/2 were comparable in an Asian population receiving a single dose of sitagliptin 100 mg or 500 mg tablets alone or in combination with metformin [23–26]. Sitagliptin safety profile, tolerability, PK, and pharmacodynamics (PD) were evaluated in single doses ranging from 1.5 mg to 600 mg. The PK parameters found in these studies were in line with current results [11].

Table 2

A comparison of the mean plasma concentration/time profiles of sitagliptin test and reference formulations in these 25 healthy male volunteers is represented in Figure 1 (all data points below the limit of quantification were entered in as zero and were included as zero in the calculation of means). The current results showed that the median T_max was comparable for both formulations. Sitagliptin elimination occurred gradually over the sampling interval of 48-hours. No significant difference was found in C_max, AUC_0–inf, or AUC_0–48 between the test and reference formulations based on the multivariate ANOVA statistical analysis. The 90% CIs of the Ln-transformed Cmax, AUC_0–inf, and AUC_0–48, were 89.2%–06.0%, 100.4%–103.5%, and 100.8%–104.0%, respectively. The two-sided 90% CIs of Ln-transformed C_max, AUC_0-inf, and AUC_0–48 of sitagliptin were within the BE acceptance range of 80%–125%, as defined by the ASEAN Guideline for the Conduct of Bioequivalence Studies [27]. Therefore, the test formulation successfully met the acceptance criteria for a BE study.

The current study involved only Caucasian participants. This might influence the generalizability of the study findings in other populations. Furthermore, only male volunteers were recruited, limiting the ability to extrapolate the PK parameters to the female population. Inter-individual variability was accounted for in the randomized crossover study design, therefy limiting its potential impact on the BE of the study products. With these potential limitations, it was concluded that the PK profiles of study products in terms of absorption, distribution, metabolism, and elimination were comparable. However, no investigation of drug PD was carried out in the current study. This would be a potential topic for future studies involving racially and sexually diverse actual diabetic patient populations.

Conclusions

The present study found that single doses of the test and reference formulations, each containing 100 mg sitagliptin in the form of sitagliptin hydrochloride monohydrate and sitagliptin phosphate monohydrate, respectively produced drug concentration/time curves under fasting conditions that met regulatory requirements for declaring the products to be bioequivalent.

Funding sources

This work was financially supported by the Duopharma Biotech Berhad.

Competing interests: CWL, ES, KMY, MSS, SRSAR, KS, MZJ, SA, and AA are employees of Duopharma, RFT is an employee of ACDIMA BioCenter that was paid to perform the study for Duopharma.

Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Chuei Wuei Leong¹, PhD
Elton Sagim¹,BBiomedSc
Kar Ming Yee¹, BPharm
Muhammad Shalhadi Saharuddin¹, BSc
Sharifah Radziah Syed Abd Rahim¹, MSc
Khairil Sabri¹, BSc
Mohd Zulhairi Jamaluddin¹, BSc
Shahnun Ahmad¹, MBBS
Atiqah Amran¹, BSc
Rabab F Tayyem², PhD

¹Duopharma Innovation Sdn Bhd, Selangor,

No. 2, Jalan Saudagar U1/16, Zon Perindustrian Hicom Glenmarie, Seksyen U1, Shah Alam 40150, Darul Ehsan, Malaysia
²ACDIMA BioCenter, Amman 11190, Jordan

References
1. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119.
2. Lin X, Xu Y, Pan X, Xu J, Ding Y, Sun X, et al. Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025. Sci Rep. 2020;10(1):14790.
3. Vijayakumar TM, Jayram J, Meghana Cheekireddy V, Himaja D, Dharma Teja Y, Narayanasamy D. Safety, efficacy, and bioavailability of fixed-dose combinations in type 2 diabetes mellitus: a systematic updated review. Curr Ther Res Clin Exp. 2017;84:4-9.
4. Stumvoll M, Goldstein BJ, Van Haeften TW. Type 2 diabetes: principles of pathogenesis and therapy. Lancet. 2005;365(9467):1333-46.
5. Albitar O, Harun SN, Abidin NE, Tangiisuran B, Zainal H, Looi I, et al. Predictors of recurrent ischemic stroke in obese patients with type 2 diabetes mellitus: a population-based study. J Stroke Cerebrovasc Dis. 2020;29(10):105173.
6. Dhillon S. Sitagliptin: a review of its use in the management of type 2 diabetes mellitus. Drugs. 2010;70(4):489-512.
7. Scott LJ. Sitagliptin: a review in type 2 diabetes. Drugs. 2017;77(2):209-24.
8. Karasik A, Aschner P, Katzeff H, Davies MJ, Stein PP.Sitagliptin, a DPP-4 inhibitor for the treatment of patients with type 2 diabetes: a review of recent clinical trials. Curr Med Res Opin. 2008;24(2):489-96.
9. Pfeiffer AF, Klein HH. The treatment of type 2 diabetes. Dtsch Arztebl Int. 2014;111(5):69-82.
10. Bergman AJ, Stevens C, Zhou YY, Yi B, Laethem M, De Smet M, et al. Pharmacokinetic and pharmacodynamic properties of multiple oral doses of sitagliptin, a dipeptidyl peptidase-IV inhibitor: a double-blind, randomized, placebo-controlled study in healthy male volunteers. Clin Ther. 2006;28(1):55-72.
11. Herman GA, Stevens C, Van Dyck K, Bergman A, Yi B, De Smet M, et al. Pharmacokinetics and pharmacodynamics of sitagliptin, an inhibitor of dipeptidyl peptidase IV, in healthy subjects: results from two randomized, double-blind, placebo-controlled studies with single oral doses. Clin Pharmacol Ther. 2005;78(6):675-88.
12. Vincent SH, Reed JR, Bergman AJ, Elmore CS, Zhu B, Xu S, et al. Metabolism and excretion of the dipeptidyl peptidase 4 inhibitor [14C]sitagliptin in humans. Drug Metab Dispos. 2007;35(4):533-8.
13. Bergman A, Ebel D, Liu F, Stone J, Wang A, Zeng W, et al. Absolute bioavailability of sitagliptin, an oral dipeptidyl peptidase-4 inhibitor, in healthy volunteers. Biopharm Drug Dispos. 2007;28(6):315-22.
14. Bergman AJ, Cote J, Yi B, Marbury T, Swan SK, Smith W, et al. Effect of renal insufficiency on the pharmacokinetics of sitagliptin, a dipeptidyl peptidase-4 inhibitor. Diabetes Care. 2007;30(7):1862-4.
15. Charoo NA, Abdallah DB, Bakheit AA, Haque KU, Hassan HA, Abrahamsson B, et al. Biowaiver monograph for immediate-release solid oral dosage forms: sitagliptin phosphate monohydrate. J Pharm Sci. 2022;111(1):2-13.
16. Zakowiecki D, Edinger P, Papaioannou M, Hess T, Kubiak B, Terlecka A. Exploiting synergistic effects of brittle and plastic excipients in directly compressible formulations of sitagliptin phosphate and sitagliptin hydrochloride. Pharm Dev Technol. 2022;27(6):702-13.
17. Boddu R, Vadla HC, Prathap VR, Kothamasu U, Rallabandi BC, Gannu R, et al. Development of an in vitro-in vivo correlation for sitagliptin and metformin prolonged-release tablet formulations. Turk J Pharm Sci. 2021;18(2):233-41.
18. Tsume Y, Mudie DM, Langguth P, Amidon GE, Amidon GL. The Biopharmaceutics Classification System: subclasses for in vivo predictive dissolution (IPD) methodology and IVIVC. Eur J Pharm Sci. 2014;57:152-63.
19. Drugs.com. Januvia [homepage on the Internet]. [cited 2022 Nov 29]. Available from: https://www.drugs.com/pro/januvia.html#s-34089-3
20. Fediuk DJ, Matschke K, Liang Y, Pelletier KB, Wei H, Shi H, et al. Bioequivalence of ertugliflozin/sitagliptin fixed-dose combination tablets and coadministration of respective strengths of individual components. Clin Pharmacol Drug Dev. 2019;8:884-94.
21. Migoya EM, Miller JL, Gutierrez M, Zheng W, Johnson-Levonas AO, Liu Q, et al. Bioequivalence of sitagliptin/metformin fixed-dose combination tablets and concomitant administration of sitagliptin and metformin in healthy adult subjects: a randomized, open-label, crossover study. Clin Drug Investig. 2010;30(12):855-66.
22. Loh GOK, Wong EYL, Tan YTF, Lee YL, Pang LH, Chin MC, et al. Simple and rapid LC-MS/MS method for determination of sitagliptin in human plasma and application to bioequivalence study. J Chromatogr B Analyt Technol Biomed Life Sci. 2020;1159:122337.
23. Reddy S, Ahmed I, Ahmad I, Mukhopadhyay A, Thangam S. Development and validation of a method for simultaneous estimation of metformin and sitagliptin in human plasma by LC–MS-MS and its application in a bioequivalence study. J Chromatogr Sci. 2015;53(9):1549-56.
24. Burugula L, Mullangi R, Pilli NR, Makula A, Lodagala DS, Kandhagatla R. Simultaneous determination of sitagliptin and simvastatin in human plasma by LC-MS/MS and its application to a human pharmacokinetic study. Biomed Chromatogr. 2013;27(1):80-7.
25. Thao NNN, Hieu NN, Tho DCMV, Loan TTT, Tuan ND. Development, validation, and application for simultaneous assay of metformin and sitagliptin in human plasma by liquid chromatography? Syst Rev Pharm. 2020;11(2):6-13.
26. Shi P, Liu X, Li T, Sun F-Fei, Liu Y-Ping, Liu S-Qin, et al. Pharmacokinetics and bioequivalence of sitagliptin phosphate/metformin hydrochloride tablets in healthy chinese subjects: a randomized, open-label, crossover study. Drugs R D. 2022;22(1):15-23.
27. National Pharmaceutical Regulatory Agency (NPRA). Ministry of Health Malaysia. ASEAN guidelines: the conduct of bioequivalence studies. 2015 [homepage on the Internet]. [cited 2022 Nov 29]. Available from: https://www.npra.gov.my/images/reg-info/BE/BE_Guideline_FinalMarch2015_endorsed_22PPWG.pdf

Author for correspondence: Chuei Wuei Leong, PhD, Formulation and R & D Technologies, Duopharma Innovation Sdn Bhd, No. 2, Jalan Saudagar U1/16, Zon Perindustrian Hicom Glenmarie, Seksyen U1, Shah Alam 40150, Selangor, Daryl Ehsan, Malaysia

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 19/07/2024

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Pharmacokinetic bioequivalence of sitagliptin phosphate tablet formulations: a randomized, open-label, crossover study in healthy volunteers

Posted on November 24, 2022

Author byline as per print journal: Chuei Wuei Leong¹, PhD; Elton Sagim¹, BBiomedSc; Kar Ming Yee¹, BPharm; Muhammad Shalhadi Saharuddin¹, BSc; Nik Mohd Zulhakimi Nik Abdullah¹, BSc; Noramirah Farhanah Saberi¹, BSc; Rajavikraman Boopathy¹, DipSc; Shahnun Ahmad¹, MBBS; Atiqah Amran¹, BSc; Raman Batheja², PhD; Rajan Sharma²>, MBBS; Kiran Kumar Vuppalavanchu², MPharm

Introduction/Study Objectives: The aim of the current study is to assess the rate and extent of absorption of a test and reference formulation containing sitagliptin.
Methods: An open-label, balanced, randomized, two-treatment, two-period, two-sequence crossover study was implemented to investigate the pharmacokinetic bioequivalence of a test and reference tablet products both containing a single dose of sitagliptin 100 mg in 28 healthy volunteers under fasting conditions. A total of twenty blood samples were obtained at pre-dose and multiple time intervals post-dose throughout the 48 hours sampling period. Sitagliptin concentrations were analysed using an LC-MS/MS validated method following a solid phase plasma extraction step. Sitagliptin pharmacokinetic parameters estimated with non-compartmental pharmacokinetic analysis were compared between the test and reference formulations with a multivariate analysis of variance.
Results and Discussion: The differences between the reference and test formulations in terms of area under the curve, 0 to infinity (AUC_0-inf), AUC_0-48, and the maximum concentration (C_max) were found to be not significant. The 90% confidence intervals of sitagliptin Ln-transformed AUC_0-inf, AUC_0-48, and C_max, were within the pharmacokinetic bioequivalence acceptance range of 80%–125%. Conclusion: The test formulation of sitagliptin was bioequivalent in terms of exposure to the reference formulation in healthy volunteers under fasting conditions.

Submitted: 15 September 2022; Revised: 7 November 2022; Accepted: 21 November 2022; Published online first: 5 December 2022

Introduction/Study Objectives

Diabetes mellitus is a multifactorial disease impacting different organ systems [1]. Until 2021, diabetes mellitus has affected 536.6 million people (10.5% of the world’s population between 20–79 years old). These numbers are expected to rise to 783.2 million people (12.1% of the world’s population), leading to severe health and economic burden [2]. Type 2 diabetes mellitus (T2DM) accounted for more than 95% of diabetes mellitus incidents [3]. T2DM is characterized by cells’ resistance to insulin resulting in elevated blood glucose levels [1] and is associated with high morbidity and mortality mainly due to its microvascular and macrovascular complications [4, 5]. T2DM requires effective glycaemic control generally achieved by lifestyle modifications and oral hypoglycaemic agents, which are considered to be the first line, especially when the β cells further deteriorate as the disease progresses with time [1].

Sitagliptin is a potent and selective dipeptidyl-peptidase (DPP-4) inhibitor, listed in 2017 among the top 20 drugs for T2DM treatment [6]. Like other DPP-4 inhibitors, sitagliptin deactivates the glucagon-like peptide-1 (GLP-1) and the glucose-dependent insulinotropic polypeptide, which increases and extends the activity of incretin resulting in a glucose-dependent secretion of insulin and inhibition in glucagon [7]. Sitagliptin decreases not only the HbA1c but also the fasting and postprandial glucose [8]. Furthermore, it is safe to be used in combination with other oral hypoglycaemic agents with no additional risk of hypoglycaemia or weight gain [9].

Sitagliptin is absorbed rapidly with a median time to the maximum concentration (T_max) of 1–4 hours and an elimination half-life (T_1/2) of 8–14 hours [10, 11]. The area under the curve (AUC) of sitagliptin was found to increase in a dose-dependent manner in healthy volunteers [11], and its absolute bioavailability was 87% [12, 13]. The metabolism pathways of sitagliptin are mainly through oxidation in the liver via cytochrome P450 (CYP) 3A4 isoenzymes, with a secondary role from CYP2C8 [12]. Sitagliptin is excreted unchanged in urine (87%) and feces (13%) [12, 13]. Furthermore, it undergoes active tubular secretion in the kidney with a renal clearance recorded as 388 mL/min [11], which is why it can be foreseen that the pharmacokinetics of sitagliptin are largely affected by renal function [14]. On the other hand, in the presence of a creatinine clearance between 50 mL/min and 80 mL/min, classified as a mild renal impairment, no dose adjustment is needed because it was not found to have any clinically significant impact on sitagliptin pharmacokinetics [14].

Phase I clinical studies failed to demonstrate the pharmacokinetic interactions between sitagliptin and simvastatin, metformin, oral contraceptives, warfarin, glyburide, or rosiglitazone likely due to the sitagliptin’s lower affinity for CYP3A4, CYP2C8, and CYP2C9 [15–20]. Digoxin AUC_(0–24) was found to be increased by 11% and 18% with the administration of 100 mg and 200 mg sitagliptin, respectively [21]. However, it was not likely to be clinically significant [21]. The absence of interactions between 83 concurrently administered medications and sitagliptin was also demonstrated in a population pharmacokinetic model of phase I and phase IIb studies [22].

From a pharmaceutical perspective, the generic formulation can produce equally effective treatments potentially at lower cost, provided that it has identical active pharmaceutical ingredients and a comparable pharmacokinetic profile [23]. This study aimed to evaluate the bioequivalence in terms of exposure of a test formulation with a reference formulation each containing sitagliptin phosphate monohydrate equivalent to 100 mg sitagliptin. The study was conducted in fulfillment of the requirements by the regulatory authorities to market the test formulation.

Methods

Study design

A study design of an open-label, balanced, randomized, two-treatment, two-period, two-sequence crossover in healthy adult human volunteers was employed to evaluate the pharmacokinetic bioequivalence of a two formulation of sitagliptin 100 mg. The two periods were separated by a washout period of five days.

The study was conducted at VerGo Pharma Research Pvt Ltd (Division VerGo Clinicals), Goa, India, in accordance with the Declaration of Helsinki, the International Conference on Harmonization–Good Clinical Practice, and the ASEAN Guideline for the Conduct of Bioequivalence Studies. This study was approved by Aavishkar Ethics Committee (Research ID: 789-18) on 22 June 2020. The study was also registered in the Thai Clinical Trial Registry (TCTR20220621004) on 20 June 2022. Prior to their enrolment in the study, informed consents were obtained from the subjects.

Study population

Recruitment of volunteers was carried out based on the fulfillment of the inclusion criteria of: 1) healthy, assessed by the medical check-up (medical history, basic medical check-up, electrocardiogram (ECG), and laboratory findings (complete blood count, serological tests, biochemical tests, and urine analysis) performed prior to participation; 2) adults aged between 18 yrs and 55 yrs; 3) body mass index (BMI) of 18.5 kg/m² to 30 kg/m² with weight not less than 50 kg for males and 45 kg for females; 4) non-pregnant women; 5) non-smokers or smokers with less than ten cigarettes per day; 6) non-alcoholic individuals. Participants taking any prescription medications for the last 14 days or any over-the-counter medication for the last seven days before the initiation of the study; having any allergies or hypersensitivity to sitagliptin, those who consumed grapefruit juice in the 48 hours or caffeinated drinks 24 hours before the initiation of the study, and participants with drug abuse were excluded.

Based on the literature, the maximum intra-subject coefficient of variation (ISCV) in C_max was found to be 19% [24] and considering a power of at least 80% and a significance level of 5%, the sample size of 28 subjects was considered to be sufficient to establish pharmacokinetic bioequivalence between the formulations considering possible withdrawal and dropouts.

Study products and administration

In the present study, the pharmacokinetic bioequivalence of Fortesia^® tablets (containing 100 mg of sitagliptin) manufactured by Duopharma, Malaysia (test formulation) was compared with Januvia^® tablets (containing 100 mg of sitagliptin) manufactured by Merck Sharp & Dohme Ltd, England (reference formulation). After overnight fasting of at least 10 hours, volunteers were randomly allocated to take the test or reference products with 240 mL of water. Participants were instructed to remain seated for two hours after receiving the dose of the test or reference products. All participants received standard meals at a fixed schedule during the course of the study.

Sampling

A total of 20 blood samples (4 mL each) were collected from each volunteer at pre-dose and 0.5, 1, 1.3, 1.7, 2, 2.3, 2.7, 3, 3.5, 4, 4.5, 5, 6, 9, 12, 16, 24, 34, and 48 hours post-dose into K₂-ethylenediaminetetraacetic acid vacutainers. Centrifugation was then performed at 4,000 revolutions per minute (RPM) for 10 minutes at 10°C. After its separation, plasma was stored in the freezer (-30°C ± 10°C), then transferred to the bioanalytical department of VerGo clinicals, where it was stored in a freezer (-70°C ± 15°C) until the analytical analysis was carried out.

Subject monitoring

Clinical and laboratory investigations were carried out to assess the safety and report any adverse events observed during the study. Vital were monitored at time of check in, before drug administration and at 2 hours, 6 hours, and 11 hours before check out and before each ambulatory sample collection in each period. In each period subject’s blood glucose monitoring was performed before dosing and at 1 hours, 3 hours, and 7 hours (± 30 minutes) after dosing.

Determination of sitagliptin plasma concentrations

Analytical method for estimation of sitagliptin in human plasma was developed and validated using liquid chromatography and tandem mass spectrometry (LC-MS/MS) with positive ion electrospray ionization using selected reactions monitoring (SRM) mode (Shimadzu, Japan). Plasma extraction was performed through the solid-phase extraction method using Strata™-X 33µm polymeric sorbent cartridges. 10 µL of the sample was injected via the autosampler, and separation was done using a HyPURITY C8 column (100 mm × 4.6 mm, i.d.: 5µm) at a temperature of 40°C and a 0.8 mL/min flow rate of the mobile phase consisting of acetonitrile and 0.1% formic acid (70:30, v/v). Sitagliptin and internal standard were monitored at the molecular ion 408.2–412.2 m/z and MS/MS (daughter) 235.1–239.1 m/z. Sitagliptin D4 was used as an internal standard. Analyte quantitation was performed on a triple quadrupole mass spectrometer using atmospheric pressure ionization (API), operated in multiple reaction monitoring (MRM) and positive ion mode. The method was validated in the concentration range of 2.024–800.714 ng/mL with good linearity of r² equals 0.999. The method achieved a within- and between-day CV% of less than 5.3% and 4.3%, respectively, and an accuracy of 93%–110%. Recovery was 78.2%–83.1% for both the internal standard and the analyte. The lower and upper limits of quantification (LLOQ and ULOQ) were found to be 2.0 ng/mL, and 800.7 ng/mL, respectively.

Pharmacokinetic and statistical analysis

Treatments were allocated to subjects by carrying out randomization using SAS software. To eliminate any bias resulting from the open-label study design, the bioanalytical department performing the bio-analysis was blinded for the identity of reference and test, and the sample analysts were blinded for the randomization schedule. Non-compartmental pharmacokinetic analysis was performed through the Phoenix WinNonlin version 6.3 (Pharsight Corporation, USA) to estimate pharmacokinetic parameters such as the AUC, 0 to infinity (AUC_0-inf), AUC, 0 hours to 48 hours (AUC_0-48), maximum concentration (C_max), elimination constant (K_e), T_max, and T_1/2 of the drug. Statistical analysis was performed via SAS software version 9.4 (SAS^® Institute Inc., USA, Version 9.4), where multivariate analysis of variance (ANOVA) was carried out on the Ln-transformed pharmacokinetic parameters C_max, AUC_0-48, and AUC_0-inf with treatment, period, sequence and subjects nested within the sequence as a fixed effect. The BE of the test formulation with the reference product was assessed based on an alpha value of 0.05, i.e. within a 90% confidence interval (CI).

Results and discussion

The present work investigated the pharmacokinetic bioequivalence of a test product formulation with a reference formulation both containing 100 mg of sitagliptin in 28 healthy volunteers under fasting conditions. One volunteer withdrew before receiving the dose in the first period due to a medical event (nausea followed by one episode of vomiting). Twenty-seven volunteers had completed the study, and their data were included in the analysis. Table 1 summarizes the demographic characteristics of the healthy volunteers with a mean ± standard deviation age of 27.0 ± 5.9 years and BMI of 23.1 ± 2.8 kg/m². Regarding safety, no serious adverse events were reported during the study. Two volunteers had red blood cells count below the normal range, one of them had elevated aspartate transaminase levels (AST), and another volunteer had increased eosinophils count. The reported adverse events were mild, and they resolved without any sequelae. The adverse events were unlikely due to the investigational product. The elevated AST was rarely reported with sitagliptin use only in a single case in the literature provoked by a possible interaction with the hepatitis B virus [25]. However, multiple reports of the increased eosinophils count were available and were possibly related to the sitagliptin pharmacological effect of DPP-4 inhibition [26, 27].

Table 1

The crossover study design involved five days washout step between the two periods adequate to account for at least 10 half-lives of sitagliptin to avoid the carryover phenomenon. The pharmacokinetic parameters of the test and reference formulations, i.e. AUC_0-48, AUC_0-inf, T_max, C_max, and T_1/2, are summarized in Table 2. C_max, AUC_0-inf, and AUC_0-48 values were comparable between the test and reference formulation. Additionally, intrasubject variabilities in AUC_0-48 were found to be 16.5% and 19.1%, and AUC_0-inf, 16.7% and 19.2%, and C_max, 24.1% and 27.6%, for the test and reference formulation, respectively. The pharmacokinetic profile found in other pharmacokinetic bioequivalence studies of a single dose of sitagliptin 100 mg or 500 mg tablets alone or in combination with metformin performed in the Asian population in terms of AUC_0-inf [28, 29], T_1/2 [29-31], and T_max [32] was comparable with the present results. Similar results in terms of T_max [33] and C_max [22] have also been reported in previous pharmacokinetic bioequivalence studies of a single dose of sitagliptin 50 mg [33] and 100 mg [22] tablet in American Hispanic/Latino and non-Hispanic/Latino volunteers. The current results were also in line with ones reported in European volunteers in the original study investigating the pharmacokinetics, pharmacodynamics, safety, and tolerability of single doses of sitagliptin ranging between 1.5 mg and 600 mg [11]].

Table 2

Figure 1 represents the mean plasma concentration of sitagliptin in the plasma for the test and reference formulations versus the time profiles in 27 healthy volunteers (all below the limit of quantification data points were inserted as zero and were involved in the calculation of means). The median T_max was comparable between the two formulations based on the current results. The elimination of sitagliptin occurred gradually during the sampling interval of 48-hour. The differences in C_max, AUC_0-inf, or AUC_0-48 between the reference and test formulation were found to be not significant based on the multivariate ANOVA statistical analysis. The 90% CIs of the Ln-transformed AUC_0-48, AUC_0-inf, and Cmax, were 99.2%–103.3%, 99.2%–103.2%, and 95.6%–108.7%, respectively. The two-sided 90% CIs of Ln-transformed AUC_0-48, AUC_0-inf, and Cmax of sitagliptin were within the pharmacokinetic bioequivalence acceptance range of 80%–125%, according to the ASEAN Guideline for the Conduct of Bioequivalence Studies [34].

The pharmacokinetic profile of sitagliptin found in the current study may represent the Asian population as only Asian participants were included affecting the generalizability of the results in different populations. However, the inter-individual variability was addressed in the randomized crossover study design eliminating its effect on the pharmacokinetic bioequivalence of the study products, i.e. it can be concluded that the pharmacokinetic profiles of test and reference products were similar in terms of absorption, distribution, metabolism, and elimination. The pharmacodynamic bioequivalence was not investigated in the current study and could be a potential topic for future studies in patients as complementary to the exposure term.

Conclusion

The pharmacokinetic bioequivalence of a single dose test product with a reference product, each containing 100 mg sitagliptin under fasting conditions, was confirmed in the present study in terms of AUC_0-inf, AUC_0-48, and C_max. The 90% confidence intervals of sitagliptin Ln-transformed AUC_0-inf, AUC_0-48, and C_max, were within the pharmacokinetic bioequivalence acceptance range of 80%–125%. The study was in fulfillment of the requirements by the regulatory authorities to market the test formulation.

Funding sources

This work was financially supported by Duopharma Biotech Berhad.

Competing interests: CWL, ES, KMY, MSS, NMZNA, NFS, RB, SA, and AA are employees of Duopharma. RB, RS, and KKV are employees of VerGo Pharma Research.

Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Chuei Wuei Leong¹, PhD
Elton Sagim¹, BBiomedSc
Kar Ming Yee¹, BPharm
Muhammad Shalhadi Saharuddin¹, BSc
Nik Mohd Zulhakimi Nik Abdullah¹, BSc
Noramirah Farhanah Saberi¹, BSc
Rajavikraman Boopathy¹, DipSc
Shahnun Ahmad¹, MBBS
Atiqah Amran¹, BSc
Raman Batheja², PhD
Rajan Sharma², MBBS
Kiran Kumar Vuppalavanchu², MPharm

¹Duopharma Innovation Sdn Bhd, No. 2, Jalan Saudagar U1/16, Zon Perindustrian Hicom Glenmarie, Seksyen U1, Shah Alam, 40150, Selangor, Darul Ehsan, Malaysia
²VerGo Pharma Research Pvt Ltd (Division VerGo Clinicals), Goa 403110, India

References
1. Vijayakumar TM, Jayram J, Meghana Cheekireddy V, Himaja D, Dharma Teja Y, Narayanasamy D. Safety, efficacy, and bioavailability of fixed-dose combinations in type 2 diabetes mellitus: a systematic updated review. Curr Ther Res. 2017;84:4-9.
2. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119.
3. Liu J, Ren ZH, Qiang H, Wu J, Shen M, Zhang L, et al. Trends in the incidence of diabetes mellitus: results from the Global Burden of Disease Study 2017 and implications for diabetes mellitus prevention. BMC Public Health 2020;20(1):1415.
4. Faselis C, Katsimardou A, Imprialos K, Deligkaris P, Kallistratos M, Dimitriadis K. Microvascular complications of type 2 diabetes mellitus. Curr Vasc Pharmacol. 2019;18(2):117-24.
5. Albitar O, Harun SN, Abidin NE, Tangiisuran B, Zainal H, Looi I, et al. Predictors of recurrent ischemic stroke in obese patients with type 2 diabetes mellitus: a population-based study. J Stroke Cerebrovasc Dis. 2020;29(10):105173.
6. Kazi M, Alqahtani A, Ahmad A, Noman OM, Aldughaim MS, Alqahtani AS, et al. Development and optimization of sitagliptin and dapagliflozin loaded oral self-nanoemulsifying formulation against type 2 diabetes mellitus. Drug Deliv. 2020;28(1):100-14.
7. Scott LJ. Sitagliptin: a review in type 2 diabetes. Drugs. 2017;77(2):209-24.
8. Dey J. SGLT2 inhibitor/DPP-4 inhibitor combination therapy – complementary mechanisms of action for management of type 2 diabetes mellitus. Postgrad Med. 2017;129(4):409-20.
9. Pfeiffer AF, Klein HH. The treatment of type 2 diabetes. Dtsch Arztebl Int. 2014;111(5):69-82.
10. Bergman AJ, Stevens C, Zhou YY, Yi B, Laethem M, De Smet M, et al. Pharmacokinetic and pharmacodynamic properties of multiple oral doses of sitagliptin, a dipeptidyl peptidase-IV inhibitor: a double-blind, randomized, placebo-controlled study in healthy male volunteers. Clin Ther. 2006;28(1):55-72.
11. Herman GA, Stevens C, Van Dyck K, Bergman A, Yi B, De Smet M, et al. Pharmacokinetics and pharmacodynamics of sitagliptin, an inhibitor of dipeptidyl peptidase IV, in healthy subjects: results from two randomized, double-blind, placebo-controlled studies with single oral doses. Clin Pharmacol Ther. 2005;78(6):675-88.
12. Vincent SH, Reed JR, Bergman AJ, Elmore CS, Zhu B, Xu S, et al. Metabolism and excretion of the dipeptidyl peptidase 4 inhibitor [14C]sitagliptin in humans. Drug Metab Dispos. 2007;35(4):533-8.
13. Bergman A, Ebel D, Liu F, Stone J, Wang A, Zeng W, et al. Absolute bioavailability of sitagliptin, an oral dipeptidyl peptidase-4 inhibitor, in healthy volunteers. Biopharm Drug Dispos. 2007;28(6):315-22.
14. Bergman AJ, Cote J, Yi B, Marbury T, Swan SK, Smith W, et al. Effect of renal insufficiency on the pharmacokinetics of sitagliptin, a dipeptidyl peptidase-4 inhibitor. Diabetes Care. 2007;30:1862-4.
15. Mistry GC, Bergman AJ, Luo WL, Cilissen C, Haazen W, Davies MJ, et al. Multiple-dose administration of sitagliptin, a dipeptidyl peptidase-4 inhibitor, does not alter the single-dose pharmacokinetics of rosiglitazone in healthy subjects. J Clin Pharmacol. 2007;47(2):159-64.
16. Wright DH, Herman GA, Maes A, Liu Q, Johnson-Levonas AO, Wagner JA. Multiple doses of sitagliptin, a selective DPP-4 inhibitor, do not meaningfully alter pharmacokinetics and pharmacodynamics of warfarin. J Clin Pharmacol. 2009;49(10):1157-67.
17. Mistry GC, Bergman AJ, Zheng W, Hreniuk D, Zinny MA, Gottesdiener KM, et al. Sitagliptin, an dipeptidyl peptidase-4 inhibitor, does not alter the pharmacokinetics of the sulphonylurea, glyburide, in healthy subjects. Br J Clin Pharmacol. 2008;66(1):36-42.
18. Krishna R, Bergman A, Larson P, Cote J, Lasseter K, Dilzer S, et al. Effect of a single cyclosporine dose on the single-dose pharmacokinetics of sitagliptin (MK-0431), a dipeptidyl peptidase-4 inhibitor, in healthy male subjects. J Clin Pharmacol. 2007;47:165-74.
19. Herman GA, Bergman A, Yi B, Kipnes M. Tolerability and pharmacokinetics of metformin and the dipeptidyl peptidase-4 inhibitor sitagliptin when co-administered in patients with type 2 diabetes. Curr Med Res Opin. 2006;22(10): 1939-47.
20. Bergman AJ, Cote J, Maes A, Zhao JJ, Roadcap BA, Sun L, et al. Effect of sitagliptin on the pharmacokinetics of simvastatin. J Clin Pharmacol. 2009;49(4): 483-8.
21. Miller JL, Migoya E, Talaty JE, Bergman AJ, Xu Y, Zheng W, et al. The effect of MK-0431 on the pharmacokinetics of digoxin after concomitant administration for 10 days in healthy subjects. Clin Pharmacol Ther. 2006;79(2):P24-P24.
22. Fediuk DJ, Matschke K, Liang Y, Pelletier KB, Wei H, Shi H, et al. Bioequivalence of ertugliflozin/sitagliptin fixed-dose combination tablets and coadministration of respective strengths of individual components. Clin Pharmacol Drug Dev. 2019;8(7):884-94.
23. Leong CW, Yee KM, Nalaiya J, Kassim Z, Rahim SRSA, Ahmad S, et al. Pharmacokinetics and bioequivalence of 2 azithromycin tablet formulations: a randomized, open-label, 2-stage crossover study in healthy volunteers. Clin Pharmacol Drug Dev. 2022;11(9):1078-83.
24. Medicines & Healthcare products Regulatory Agency. Public Assessment Report. Sitapren 25 mg, 50 mg and 100 mg film coated tablets (Sitagliptin) [homepage on the Internet]. [cited 2022 Nov 7]. Available from: https://mhraproducts4853.blob.core.windows.net/docs/0de741dc4a32ba964a581c7aa44a91a69a9e778f.
25. Shafqet M. Sitagliptin: a rare cause of drug-induced liver injury: 424. Am J Gastroenterol. 2014;109:S127.
26. Hollande C, Boussier J, Ziai J, Nozawa T, Bondet V, Phung W, et al. Inhibition of the dipeptidyl peptidase DPP4 (CD26) reveals IL-33-dependent eosinophil-mediated control of tumor growth. Nat Immunol. 2019;20(3):257-64.
27. Baraniuk JN, Jamieson MJ. Rhinorrhea, cough and fatigue in patients taking sitagliptin. Allergy Asthma Clin Immunol. 2010;6(1):8.
28. Reddy S, Ahmed I, Ahmad I, Mukhopadhyay A, Thangam S. Development and validation of a method for simultaneous estimation of metformin and sitagliptin in human plasma by LC–MS-MS and its application in a bioequivalence study. J Chromatogr Sci. 2015;53(9):1549-56.
29. Burugula L, Mullangi R, Pilli NR, Makula A, Lodagala DS, Kandhagatla R. Simultaneous determination of sitagliptin and simvastatin in human plasma by LC-MS/MS and its application to a human pharmacokinetic study. Biomed Chromatogr. 2013;27(1):80-7.
30. Thao NNN, Hieu NN, Tho DCMV, Loan TTT, Tuan ND. Development, validation, and application for simultaneous assay of metformin and sitagliptin in human plasma by liquid chromatography? Tandem Mass Spectrometry. Syst Rev Pharm. 2020;11(2):6-13.
31. Shi P, Liu X, Li T, Sun F fei, Liu Y ping, Liu S qin, et al. Pharmacokinetics and bioequivalence of sitagliptin phosphate/metformin hydrochloride tablets in healthy chinese subjects: a randomized, open-label, crossover study. Drugs R D. 2022;22(1):15-23.
32. Loh GOK, Wong EYL, Tan YTF, Lee YL, Pang LH, Chin MC, et al. Simple and rapid LC-MS/MS method for determination of sitagliptin in human plasma and application to bioequivalence study. J Chromatogr B Analyt Technol Biomed Life Sci. 2020;1159:122337.
33. Migoya EM, Miller JL, Gutierrez M, Zheng W, Johnson-Levonas AO, Liu Q, et al. Bioequivalence of sitagliptin/metformin fixed-dose combination tablets and concomitant administration of sitagliptin and metformin in healthy adult subjects: a randomized, open-label, crossover study. Clin Drug Investig. 2010;30(12):855-66.
34. National Pharmaceutical Regulatory Agency (NPRA). Ministry of Health Malaysia. ASEAN Guideline for the conduct of bioequivalence studies. 2015 [homepage on the Internet]. [cited 2022 Nov 7]. Available from: https://www.npra.gov.my/images/reg-info/BE/BE_Guideline_FinalMarch2015_endorsed_22PPWG.pdf

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 26/07/2024

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Social trust and regional variation in the adoption of biosimilars in Italy and Germany

Posted on September 8, 2022

Introduction/Study Objectives: Adoption of biosimilars has fallen below projections, despite the vigorous implementation of economic incentives, thereby highlighting the importance of behavioural factors such as social trust. This paper analyses biosimilar adoption across provinces in Italy and Germany, which evince strong variation in social trust, and across nations in Europe.
Methods: Data for 2020 biosimilar adoption for Italian provinces were obtained from the national pharmaceutical organization and for German states from the association of biosimilar manufacturers. Social trust was coded for Italy and Germany using historical metrics; political trust was coded using the Quality of Government Index (QGI). Multivariable methods were used to ascertain the association between adoption, social trust, political trust, and income per capita. Regressions also were conducted using data at the national level for 20 European nations. The study includes two biologicals for chronic immunological conditions, three biologicals for acute cancer treatments, and their 20 biosimilars.
Results: Adoption of biosimilars was much lower in regions suffering from low social trust and low trust in government, respectively, with penetration falling below the national median in seven out of eight provinces in southern Italy and in all seven provinces in eastern Germany. Rates of adoption are 21.5 percentage points higher in northern than in southern Italy and 5.2 points higher in western than in eastern Germany, controlling for other relevant factors. Provinces with low values on the QGI had significantly lower adoption than provinces with high citizen trust in government.
Conclusion: Economic incentives to promote adoption of biosimilars must ensure that the benefits accrue to the populations most affected, thereby enhancing social trust and cooperation.

Submitted: 2 August 2022; Revised: 13 September 2022; Accepted: 16 September 2022; Published online first: 26 September 2022

Introduction/Study Objectives

Biologicals account for the most rapidly rising component of drug spending, and public policies in many nations have placed their hopes for cost moderation on competition from therapeutically equivalent but lower price biosimilars. However, adoption has fallen short of the potential, despite the vigorous implementation of economic incentives, highlighting the role of behavioural factors such as citizens’ trust in one another, referred to as social trust, and trust in government policymakers, referred to as political trust. The importance of trust has been evident in recent years with the uneven adoption of preventive measures against COVID-19 and is of salience for biosimilars. Patients must trust the clinical experts who declare biosimilars to be as safe and effective as the reference biologicals. They also must trust that the financial savings will be used by national health systems to fund desirable goals, such as additional clinical staff, rather than be diverted to waste and fraud.

This paper analyses the association between trust and adoption within Italy and Germany, which for historical reasons evince strong regional variations in social and political trust. If the promise of biosimilars lies in financial savings, one would assume that adoption would be pursued more vigorously in low-income southern Italy and eastern Germany than in their more favourably placed northern and western regions. To the extent social and political trust promote acceptance of biosimilars, however, adoption would be expected to be higher in high-trust northern Italy and western Germany than in low-trust southern and eastern regions. Similar considerations would affect expectations for the pattern of adoption across nations within Europe. The association between trust and adoption is complex and merits study using distinct measures of social and political trust, multiple nations with distinct geographic patterns of trust, and distinct categories of biologicals that require different patterns of utilization, respectively.

Data and methods

Choice of study regions
Italy and Germany have well-documented regional variation in social and political trust, effective political institutions, and economic performance. Southern Italy long suffered from foreign domination and autocratic political institutions that impeded the development of civic engagement and economic development, compared to northern regions with more republican civic traditions. Eastern Germany was subjected to domination by the Soviet Union for 40 years after the end of World War II, with low levels of social and political trust and economic development. It compares unfavourably to the more democratic and prosperous western regions that were occupied by Allied forces after the war.

This study collected 2020 data from regulatory agencies and health insurance plans to quantify within-nation variation in biosimilar market shares in Italy and Germany and cross-nation variation in Europe as a whole. Sales data for individual biologicals and biosimilars from each of the 21 provinces and autonomous regions in Italy were obtained from the Italian Medicines Agency (Agenzia Italiana del Farmaco, AIFA) [1, 2]. The AIFA data were supplemented by reports from pharmaceutical industry sources, by published case studies of selected provinces, and by interviews with leaders in regional health authorities and hospitals [3]. Data on biologicals and biosimilars sales for each of the 17 German states and city-states were obtained from ProBiosimilars, an industry umbrella organization [4]. The German data were supplemented by annual reports on drug use and spending, special analyses sponsored by the regional (Allgemeine Ortskrankenkassen, AOK) Sickness Funds, scholarly publications, documents from other Sickness Funds, industry associations, and consulting firms, and by interviews [5-8]. Data on adoption at the national level for 20 Member States in the European Union were obtained from an annual report from IQVIA.

The analysis of Italian regional variation builds on a major study by Robert Putnam and colleagues that compared social trust, civic engagement, political institutions, and economic outcomes in southern and northern Italy in the closing decades of the 20th century [9]. The Putnam team collected statistical data, fielded numerous surveys of politicians and the public, and conducted case studies of individual provinces over a 25-year period. They published regional maps of engagement, attitudes, entrepreneurship, and economic growth. Low levels of social trust at the provincial level were consistently associated with low levels of economic and political performance. Italy has a national single-payer healthcare financing system and a physician sector composed of hospital-employed specialists [10]. These characteristics of the Italian system partially offset regional differences in income, but there remains strong regional variation in healthcare system performance [11, 12].

The boundary between the eastern and western regions of Germany, defined by the demarcation line at the end of World War II, has served as the basis for numerous studies of social trust and economic performance [13, 14]. Emphasis has been placed on the systematic surveillance of the eastern population by the secret police, which recruited informers in every workplace and neighbourhood to undermine social bonds that were not mediated by the communist party and its affiliates [15]. Some of the cultural and economic differences between eastern and western areas of Germany preceded the war and the post-war period and reflect deeper historical differences in rates of industrialization and democratic political institutions [16].

This study supplemented the geographic and regional indicators of social trust in Italy and Germany with a major survey of political trust, conducted in 2013 by Charron and colleagues at the University of Gothenburg [17]. The 85,000 respondents were spread over all European nations and many provinces within nations. The Quality of Government Index (QGI) is based on control of corruption, rule of law, government effectiveness, and citizen voice and accountability, and is available at the provincial level for Italy and Germany and at the national level for most nations in Europe. Across Europe, the index reports comparatively high levels of trust in government in northern and western nations and comparatively low levels in southern and eastern nations. Germany scores above the European average while Italy scores substantially below the average.

The two measures of social and political trust used in this study capture distinct but complementary dimensions of the populations trust in their fellow citizens and in their political leaders. The geographic indicator (southern versus northern Italy, eastern versus western Germany) measures social trust by individuals in other people and their community, not specifically trust in government. The QGI is a measure of citizen attitudes towards government, not specifically of social trust in other individuals in their community. These two measures are complements, not substitutes, as indicators of the population’s attitudes.

Choice of biologicals and biosimilars
The importance of social and political trust for biosimilar adoption likely is greater when the patient is aware of which drug is being used, and hence may be more evident for biologicals and biosimilars self-administered at home via injection in contrast to those received in a hospital clinic via physician infusion. Trust also is important when patients initiate treatment with a biological and need to be switched to a biosimilar, in contrast to patients who begin their treatment with a biosimilar and do not need to switch. Self-injected biologicals are commonly used over long courses of treatment for patients with immunological conditions such as rheumatoid arthritis, while physician-infused biologicals commonly are used for short courses of treatment for oncologic conditions. This study included both self-injected biologicals for chronic immunological conditions and physician-infused biologicals for acute cancer treatments. The self-injected immunology biologicals, adalimumab and etanercept (brand names Humira and Enbrel), compete in Europe with 8 biosimilars, while the infused oncology biologicals, trastuzumab, bevacizumab, and rituximab (brand names Herceptin, Avastin, and Rituxan), compete with 12 biosimilars.

Methods

This study examined the patterns of biosimilar adoption at both the regional level (provinces in Italy, states in Germany) and the national level for 20 nations (number of European nations used in study). The identification of individual Italian provinces as southern and northern builds on the provincial maps published by Putnam and colleagues. The German comparison was made in terms of the line between the western Federal Republic of Germany (FDR) and eastern German Democratic Republic (DDR) that remained in place until the fall of the Berlin wall in 1989. Political trust at the provincial level in Italy and state level in Germany were measured using the QGI.

Provincial maps of Italy and state maps of Germany were coded according to the percentage of sales volumes for each of the five medications accounted for by biosimilars. The five individual biologicals and their biosimilars were combined into a sales-weighted index of overall adoption. The study examined the association between social trust, political trust, and income per capita for the sales weighted index and for each of the five medications individually.

Multivariable regression methods were used to identify the association between biosimilar market share, on the one hand, and social trust, political trust, and income per capita, on the other. Income per capita was included in the regression analyses to ascertain whether low income, and hence the need for healthcare savings, was a confounding factor in the association between adoption and the study’s measures of social and political trust. There is a strong independent association between income per capita and both social and political trust. Regression analyses also were performed at the European level using national QGI scores, national gross domestic product (GDP) per capita, and rates of biosimilar adoption for 20 nations in Europe [6]. The cross-nation analyses are presented in the online appendix. The multivariable regression analyses used the individual medication as the unit of observation, rather than the weighted index, and include controls for each treatment, with Rituxan as the reference medication.

Results

Figure 1 presents a map of the Italian provinces with their percentage rates of biosimilar adoption, using the weighted index of five medications. Rates of adoption ranged from a low of 39.2% in the rural southern province of Molise to a high of 97.5% in the rural northern province of Trento. A clear geographic demarcation is evident along the north-south lines described by the literature on political, economic, and cultural variation. Seven of the eight southern provinces exhibited rates of adoption below the national median, while nine of the 12 northern regions exhibited rates above the national median. Several provinces had rates of adoption not aligned with the north-versus-south distinction, however. The southern province of Puglia had a relatively high adoption rate due to high use of biosimilars for trastuzumab and rituximab, although use of chronic immunologic biosimilars for adalimumab and etanercept was low. The northern provinces of Liguria, Friuli and Lombardy exhibited relatively low rates of adoption. For Friuli and Lombardy, the low adoption rates extended across all five drugs, while for Liguria it was concentrated in bevacizumab.

Figure 2 presents a map of the German states and city states with their biosimilar adoption percentages, measured using the index of five medications. Adoption rates on average were much higher in Germany than in Italy, ranging from a low of 71.1% in the eastern city state of Berlin to a high of 88.4% in the western city state of Bremen. All seven of the former Soviet-dominated states exhibited rates of adoption below the German national median, while 8 of the 10 western states exhibited rates above the median. The exceptions to the general pattern are the low rates of adoption in the western states of Hamburg and Hesse.

Figure 3 plots biosimilar adoption rates for each Italian province and German state against its QGI as a measure of political trust. Provinces scoring high on the QGI generally exhibited higher rates of biosimilar adoption than do provinces and states with low public trust in government. Figure 4 plots biosimilar adoption against income per capita in Italian provinces and German states. High-income regions exhibit higher rates of adoption than do low-income regions, even though the poor regions have a greater need for the savings offered by biosimilars.

Table 1 presents multivariable regression parameters for the association between the percentage biosimilar adoption, on the one hand, and geographic indicators of social trust, political trust, and income per capita, on the other. As indicated in the first column, the geographic indicators of social trust are strongly associated with biosimilar adoption. Compared to provinces in southern Italy (the reference category), rates of adoption are 21.5 percentage points higher in northern Italy, 15.1 percentage points higher in eastern Germany, and 20.3 percentage points higher in western Germany (p < 0.001). The positive association between trust and biosimilar adoption also is evident in terms of political trust measured using the QGI, as indicated in the second column of the Table. The coefficients on the QGI range from a low of -2.42 to a high of -0.82 across Italian provinces and from a low of 0.65 to a high of 1.36 across German states. The association with biosimilar adoption is weaker than with the social trust, however. A two standard deviation increase in the QGI is associated with a 10.8 percentage point increase in adoption (p < 0.05). The association between biosimilar adoption and income per capita is presented in the third column. High-income provinces and states exhibit higher rates of adoption than less wealthy regions, with a 1,000 Euros increase in income per capita associated with a 3.20 percentage point increase in adoption (p < 0.05).

The fourth column of Table 1 presents regression coefficients when the QGI measure of political trust and the income per capita measure of economic need are included as covariates along with the geographic indicators of social trust. The association between biosimilar adoption and the geographic indicators (northern Italy and both regions of Germany in comparison to southern Italy) grows in absolute value, compared to the univariate regression results presented in the first column. The coefficient on QGI is reduced to statistical insignificance, compared to the univariate results in the second column. The coefficient on income per capita undergoes a change of sign, due to the very low levels of income in southern Italy, in comparison with the univariate results presented in the third column.

These within-nation associations between biosimilar adoption and measures of trust and income are replicated using across-nation data for Member States in the European Union, with results presented in the online Appendix.

Discussion

Italy
Italy’s national policy promoting the adoption of biosimilars, articulated in a 2018 position paper by AIFA, declared biosimilars to be therapeutically equivalent to biologicals and as recommended for new patients [18]. AIFA estimated that further adoption could fund a wide range of services for the national health system [19, 20]. Industry-oriented reports also favour biosimilar adoption, albeit without favouring mandates or exclusive product contracts [21–23].

Budgetary responsibility is allocated by the Italian healthcare financing system to the provinces, some of which then delegate responsibility to local hospitals and hospital groups. Some hospitals, in their turn, allocate a portion of the savings from biosimilar adoption to the specialty departments where most of the prescription is conducted, such as rheumatology, immunology, and oncology. Most specialist physicians in Italy are employed by a hospital. Retention of savings at the department level, rather than diffusion across the entire hospital organization, permits increased spending on staff or equipment in a manner valued by the prescribing physicians.

The ability of regional budgetary authorities and hospitals to craft effective gainsharing incentives depends on organizational scale and sophistication, which often are less developed in southern than in northern provinces. The weakness of hospital capabilities in the south may be itself a result of the regional political cultures. With respect to the healthcare system specifically, Ricciardi and Tarricone highlight weak organizational capabilities and attribute to them the decisions by southern patients to travel to northern facilities for advanced tests and procedures [24]. For example, the low uptake of biosimilars in the southern province of Puglia may be due to an unwillingness to share savings with hospitals, much less departments within hospitals. As indicated in Table 1, Puglia exhibits high rates of biosimilar penetration in oncology, where patient switching is not needed, but low rates in immunology, where it is. In contrast, the comparatively effective regional health authority in Tuscany has achieved a high biosimilar penetration rate [25]. Bertolani and Jommi have documented the uneven regional implementation of biosimilar gainsharing initiatives in Italy [26].
Physician associations may be weaker in southern than in northern Italian provinces in terms of enforcing prescription guidelines, even though the burden on physicians seeking to convince patients to switch may be greater in the south due to low social and political trust in authority. Weak professional associations leave a greater space for educational activities by pharmaceutical companies, which understandably promote higher-priced biologicals over lower-priced biosimilars. The comparatively low rate of biosimilar prescription in the northern province of Lombardy has been attributed to the lack of strong guidance on patient switching criteria by the regional physician association [27]. The comparative lack of social and political trust in southern Italian provinces may engender to a cycle of low biosimilar adoption, meagre savings, consequent deficits in regional budgets, the imposition of direct controls by national authorities, and further mistrust [28].

Germany
Germany has a national policy favouring the prescription of biosimilars as one component of a larger statutory framework promoting the ‘efficien’ use of healthcare resources. Sickness Funds, regional physician associations, drug manufacturers, and patient advocacy groups all acknowledge the imperative for stewardship of social resources, although each can interpret the mandate in its own way. Sickness Funds collaborate as well as compete with one another, sharing premium revenues to compensate for differences in enrollee risk mix and paying the same prices for physician services, hospital admissions and drugs.

The mechanisms used in Germany to attenuate pharmaceutical spending are the price negotiations conducted by the national association of Sickness Funds (GKV-SV) for novel products and the reference pricing system for follow-on products including biosimilars [29, 30]. Sickness Funds negotiate confidential rebates off the national prices, but according to interviews conducted with Fund leaders, these rebates do not vary significantly across individual Funds. Many of the Sickness Funds have membership concentrated in one or just a few provinces, but individual Funds tend to negotiate as part of multi-region associations or delegate the negotiations to consulting firms that operate at the national level.

Sickness Funds also negotiate contracts with the provincial physician associations (Kassenärztliche Vereinigung, KV) for ‘efficient’ prescribing, which includes target quotas for biosimilar prescription [31]. The enforcement mechanisms with respect to individual physicians are weak, because the Funds lack administrative mechanisms such as prior authorization and payment mechanisms based on gainsharing. The prescription quotas specified with regional physician associations cover all the physicians in the region and do not vary among Sickness Funds.

Overall, the structure of economic incentives would not appear to explain regional variation in adoption of biosimilars in Italy and Germany. A more promising explanation would highlight cultural differences among physician associations (as well as among patients) [32, 33].

Conclusion

Low levels of social trust and trust in government may be important impediments to the adoption of biosimilars, despite the potential for significant savings that can be used to finance other healthcare services. Historically disadvantaged populations such as those in southern Italy and eastern Germany may mistrust the safety and efficacy of biosimilars as part of a broader distrust of experts and institutions. They may be less inclined than their more advantaged regional counterparts to believe they will benefit from any budgetary savings. In these contexts, the potential for economic savings is outweighed by lack of social and political trust. Andersen and Griffith argue that the appropriate response to mistrust in healthcare organizations is not a doubling down on efforts to increase citizen trust but a redesign of those organizations to improve trustworthiness [34]. By extension, the appropriate response to regional variation in adoption of biosimilars is not a doubling down on economic incentives but a redesign of those incentives to ensure that the benefits accrue to the populations most affected, and that thereby enhance social and political trust.

Funding sources

Arnold Ventures (formerly, Laura and John Arnold Foundation

Competing interests: None.

Provenance and peer review: Not commissioned; externally peer reviewed.

References
1. Agenzia Italiana del Farmaco. Biosimilari: analisi della variabilita regionale. July 2021 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.aifa.gov.it/documents/20142/878552/2_AnalisiVariabilitàRegionale_gen2021-ott2021.pdf
2. Agenzia Italiana del Farmaco. Biosimilari medicines in Italy: AIFA reports updated. October 2021 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.aifa.gov.it/-/farmaci-biosimilari-in-italia-report-aifa-aggiornati-a-ottobre-2021
3. Careade I, Ornago E, Pinciroli S, Poma F, Sala E, Zaninelli M. Farmaci biologici e biosimilari. Scenari terapeutici e stima del risparmio per il sistema sanitaria italiano. Centro Studi IQVIA Italia. 2019 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://assobiotec.federchimica.it/docs/default-source/default-document-library/(iqvia)_farmaci_biologici_e_biosimilari.pdf?sfvrsn=853ad623_0
4. ProBiosimilars. Biosimilars in Zahlen 2021. Available from: https://probiosimilars.de/publikationen/biosimilars-in-zahlen/
5. Arzneiverordnungs-Report 2020. In: Schwabe U, Ludwig WD (editors). Springer 2020.
6. Troein P, Newton M, Scott K, Mulligan C. The impact of biosimilar competition in Europe. IQVIA Institute. 16 Dec 2021 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.iqvia.com/library/white-papers/the-impact-of-biosimilar-competition-in-europe-2021
7. Schröder M, Lohmüller J, Telschow C, Niepraschk-von Dollen, Zawinell A, Bauckmann J. Der GKV-Arneimittelmarkt Bericht 2020. WiDO Wissenschaftliches Intitut der AOK. Berlin 2020 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.wido.de/forschung-projekte/arzneimittel/gkv-arzneimittelmarkt/
8. Arbeitsgemeinschaft ProBiosimilars. Handbuch biosimilars 2019. Available from: https://probiosimilars.de/publikationen/handbuch-biosimilars/
9. Putnam RD, Leonardi R, Nanetti FY. Making democracy work: civic traditions in modern Italy. Princeton: Princeton University Press; 1993.
10. Donatini A. International health care system profiles: Italy. Commonwealth Fund. 2020.
11. Ricciardi W, Tarricone R. The evolution of the Italian National Health Service. Lancet. 2021;398(10317):2193-206.
12. Garattini L, Badinella Martini M, Zanetti M. The Italian NHS at regional level: same in theory, different in practice. Eur J Health Econ. 2022;23(1):1-5.
13. Kim SH. Changes in social trust: evidence from East German migrants. Soc Indic Res. 2021;155:959-81.
14. Gramlich J. How the attitudes of West and East Germans compare, 30 years after fall of Berlin wall. Pew Research Center. 18 Oct 2019.
15. Lichter A, Löffler M, Siegloch S. The long-term costs of governmental surveillance: insights from stasi spying in East Germany. J Eur Econ Assoc. 2021;19(2):741-89.
16. Becker SO, Mergele L, Woessmann L. The separation and reunification of Germany: rethinking a natural experiment interpretation of the enduring effects of communism. J Econ Perspect. 2020;34(2):143-71.
17. Charron N, Dijkstra V, Lapuente V. Regional governance matters: quality of government within European Union Member States. Reg Stud. 2014;48(1):68-90.
18. Agenzia Italiana del Farmaco. Secondo position paper AIFA sui farmaci biosimilari. 2018 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.aifa.gov.it/sites/default/files/pp_biosimilari_27.03.2018.pdf
19. Povero M, Prandelli L. Funding innovation thanks for anti-TNF biosimilars uptake: the economic impact on Italy. Farmaconomia. 2020;21(1):37-47.
20. Mennini FS, Marcellusi A, Bini C, Rotundo MA, Glunta A, Gasbarrini A, et al. The economic impact of biosimilars in Italy: a scenario analysis. Glob Reg Health Technol Assess. 2019;6(1):1-8.
21. Careade I, Ornago E, Pinciroli S, Poma F, Sala E, Zaninelli M. Farmaci biologici e biosimilari. Scenari terapeutici e stima del risparmio per il sistema sanitaria italiano. Centro Studi IQVIA Italia. 2019 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://assobiotec.federchimica.it/docs/default-source/default-document-library/(iqvia)_farmaci_biologici_e_biosimilari.pdf?sfvrsn=853ad623_0
22. Equalia, Industrie Farmaci Accessibili. Il mercato italiano dei farmaci biosimilari. Dati 2020 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.egualia.it/it/biosimilari/studi-ed-analisi/biosimilari-in-italia/mercato-italiano-report-2020.html
23. Farmindustria Centro Studi. Indicatori farmaceutici. Luglio 2021 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.farmindustria.it/app/uploads/2021/07/indicatorifarmaceutici2021-PUBBLICO.pdf
24. Ricciardi W, Tarricone R. The evolution of the Italian National Health Service. Lancet. 2021;398:2193-206.
25. Guidotti E, Vinci B, Attanasia F, Vola F. Effective tools to manage biosimilars prescription: the Italian experience. Health Policy Technol. 2021;10:41-51.
26. Bertolani A, Jommi C. Local policies on biosimilars: are they designed to optimize use of liberated resources? Generics and Biosimilars Initiative Journal (GaBI Journal). 2020;9(4):163-70. doi:10.5639/gabij.2020.0904.027.
27. Aitken M, et al. Spotlight on biosimilars: optimizing the sustainability of healthcare systems. IQVIA Institute. June 2021 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.iqvia.com/insights/the-iqvia-institute/reports/spotlight-on-biosimilars
28. Jommi C, Otto M, Armeni P, Costa F, Bertolani A. Osservatorio farmaci, report annuale per il 2020. Universitá Bocconi, Centre for Research on Health and Social Care Management. Report 41, October 2021.
29. Robinson JC. Lower prices and greater patient access – lessons from Germany’s drug-purchasing structure. N Engl J Med 2020; 382:2177-9.
30. Robinson JC, Pantelli D, Ex P. Reference pricing in Germany: implications for U.S. pharmaceutical purchasing. The Commonwealth Fund, Issue brief, February 2019.
31. Moorkens E, Barcina Lacosta T, Vulto AG, Schulz M, Gradi G, Enners S, et al. Learnings from regional market dynamics of originator and biosimilar infliximab and etanerercept in Germany. Pharmaceuticals. 2020;13(10):324.
32. Flume M. Regional management of biosimilars in Germany. Generics and Biosimilars Initiative Journal (GaBI Journal). 2016;5(3):125-27. doi:10.5639/gabij.2016.0503.031
33. Arbeitsgruppe Arzneimittelvereinbarung, Gemeinsame Information der KVWL und der Verbande der Krankenkassen in Westfalen-Lippe. Weitere Festbetrage bei den TNF-alpha-Inhibitoren. May 2021 [homepage on the Internet]. [cited 2022 Sep 13]. Available from: https://www.kvwl.de/arzt/verordnung/arzneimittel/info/agavm/tnf_alpha_inhibitoren.pdf
34. Anderson A, Griffith DM. Measuring the trustworthiness of health care organizations and systems. Milbank Quarterly. June 2022.

Author: Professor James C Robinson, PhD, MPH, Leonard D Schaeff er Professor of Health Economics, Director, Berkeley Center for Health Technology, Division Head, Health Policy and Management, University of California, School of Public Health, Berkeley, CA 94720-7360, USA

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 19/07/2024

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US prescribers’ attitudes and perceptions about biosimilars

Posted on September 8, 2022

Author byline as per print journal: Michael S Reilly, Esq; Ralph D McKibbin, MD, FACP, FACG, AGAF

Introduction: In the United States (US), a legal framework for approving biosimilars was established via the Biologics Price Competition and Innovation Act of 2009 (BPCI Act). At the time of writing (September 2022), 38 biosimilars have been approved in the US. Some biosimilars in the US can be designated as ‘interchangeable,’ which means they can be automatically substituted at the pharmacy level. In 2021, the Alliance for Safe Biologic Medicines (ASBM) surveyed prescribing physicians in the US for their views on the prescribing, substitution and interchangeability of biosimilars.
Methodology: In September 2021, the ASBM, conducted a web-based quantitative survey with 401 participants practicing medicine in the US. Prescribers were asked for their views on substitution of, as well as their familiarity with, knowledge of, attitudes to, and beliefs in, biosimilars.
Results: Most physicians are comfortable prescribing biosimilars and comfortable switching stable patients to biosimilar product. Over half of physicians are more likely to prescribe biosimilars with interchangeable status and a similar percentage are more comfortable with pharmacy-level substitution of these products. However, the majority want to keep the authority to prevent pharmacy-led substitution if they specify so. Regarding switching patients to a biosimilar for non-medical reasons, the majority were comfortable doing this themselves but fewer than half were comfortable with a third party initiating the switch. In addition, most physicians favoured a scenario where multiple products, including innovator and biosimilars are reimbursed, and biosimilars may be encouraged for new patients with no automatic substitution permitted.
Conclusion: The survey reveals that overall, American physicians are confident prescribing biosimilars. It also sheds light on how they feel about the interchangeable designation, and biological drugs switching choices made by them, pharmacists and payers.

Submitted: 16 August 2022; Revised: 17 October 2022; Accepted: 27 October 2022; Published online first: 9 October 2022

Introduction

In the US, a legal framework for approving biosimilars was established via the Biologics Price Competition and Innovation Act of 2009 (BPCI Act). The US Food and Drug Administration (FDA) approved its first biosimilar, Zarxio (filgrastim-sndz), in 2015 [1]. At the time of writing (September 2022), 38 biosimilars have since been approved by FDA [2].

FDA approval of a biosimilar is based on the ‘totality of the evidence’ from comparative analytical and functional assessments and comparative clinical (pharmacology, immunogenicity, safety and efficacy) assessments that support a conclusion of biosimilarity [3].

An approved biosimilar can also be designated as ‘interchangeable’ if it can be concluded that the biosimilar is expected to produce the ‘same clinical result as the reference product in any given patient’ and there is no increased risk in terms of safety or diminished efficacy associated with switching or alternating between the biosimilar and reference product [4]. With such designation, an interchangeable biosimilar can be substituted for its reference at the pharmacy level (where state law allows) without notification of, or permission from, the prescriber [5]. Under these circumstances, pharmacy-level substitution can be prevented if the prescriber affirms this on the prescription [6]. In most US states, it is necessary for the pharmacist to notify the patient and prescriber of the substitution having been made. FDA approved the first interchangeable biosimilar, Semglee (insulin glargine-yfgn), in July 2021 [6, 7]. As of September 2022, two additional interchangeable biosimilars have been approved [8, 9].

In 2021, the Alliance for Safe Biologic Medicines (ASBM) commissioned a web-based survey to be conducted by practitioners/physicians across the US. This was designed to document their perspectives on prescribing biosimilars, substitution and the interchangeable designation. In many ways this mirrored previous surveys carried out by the ASBM in Europe in 2013 and 2019 [10, 11]. These surveys revealed that, in Europe, awareness of biosimilars had increased between 2013 and 2019, with familiarity with biosimilars reaching 90.0% levels in 2019 compared to just 76.0% in 2013. In 2019, a strong majority of respondents (over 80.0%) felt that it is either ‘Very important’ or ‘Critical’ for them to decide which biological medicine is dispensed to their patients, representing a 10.0% increase over the results of the 2013 survey. Again, over 80.0% respondents considered authority to prevent a substitution either ‘Very important’ or ‘Critical’, another 10.0% increase over the 2013 findings. In 2019, physicians remained uncomfortable with switching a stable patient to a biosimilar for non-medical reasons. Between the two surveys there was also a sharp increase in physicians who were highly uncomfortable with a third party changing a patient’s medicine without consultation with the physician.

These ASBM surveys also draw on other previous surveys and workshops carried out across the world (Australia [12], Europe [10, 11, 13], South America [14] and the US [15, 16]) that asked for prescriber opinions on prescribing practices, naming and labelling of biologicals. In terms of naming, prescribers in Australia, Europe and the US, overall, agreed that there is a need for distinguishable non-proprietary names to be given to all medications. This current US ASBM survey makes it clear to physicians that biosimilars, as well as new originator biologicals, are distinguished from older reference originator products by means of a unique four-letter suffix representing the biosimilar manufacturer and asks for an opinion on whether these suffixes suggest or imply inferiority.

Sample characteristics and methodology

In September 2021, the ASBM conducted a web-based, quantitative survey with 401 participants practicing medicine in the US. Their therapeutic specialities were spread across: Allergy/Immunology, Dermatology, Endocrinology, Gastrointestinal, Infectious diseases, Internal medicine, Nephrology, Neurology, Oncology, Respiratory/Pulmonology, Rheumatology and Urology.

The physician panel provider uses their internal database of more than one million healthcare professionals worldwide for sampling. Also, when necessary, the physician panel provider partners with other market research companies to meet demands of healthcare clients in the industry. The market research companies go through very selective vetting process as well as training on ISO certification and market research industry standards to make sure all provide the best service to clients.

ISR’s physician panel provider uses the following channels for recruitment:

Professional conferences
Direct mail via American Medical Association (AMA) verified United States Medical Doctors (USMD) database
Online recruitment targeted at AMA verified United States Medical Doctors
Email, faxing, mailing lists of verified market research companies

All survey respondents are managed online through the market research companies’ patented, internal, proprietary system, which is ISO 26362 certified since 2011.

The questionnaires were developed as a collaboration among ASBM management, ASBM membership, and ISR management. No ‘validation’ has been conducted as the instruments do not measure higher level ‘constructs’. They are purely direct measures of opinion and attitude.

Details of respondent profile

The participants practiced medicine in states across the US, with the majority practicing in multi-specialty clinics (25.9%), academic medical centres (24.4%), and in the community setting (22.2%). The remainder practiced in private, family practice (17%) or hospitals (8.7%), see Figure 1. There was a fairly even spread of experience among the physicians, with 36.1% having a tenure period of over 20 years, 33.7% with tenure of between 11–20 years, and 30.2% with a tenure period under 10 years.

The spread of specialties practiced was fairly even, with each specialty being practiced by between 7.0%–9.2% of those that carried out the survey. As stated above, the specialties were Allergy/Immunology, Dermatology, Endocrinology, Gastrointestinal, Infectious diseases, Internal medicine, Nephrology, Neurology, Oncology, Respiratory/Pulmonology, Rheumatology, and Urology, see Figure 2.

All physicians that completed the survey said that they prescribed biologicals. Regarding the knowledge of biosimilars, the vast majority of them (97.8%) said they were either very familiar, with a complete understanding of them, or familiar with a basic understanding, however, 0.2% did say they had never heard of biosimilars.

Online survey

Prescribers were asked to consider:

Their confidence level with prescribing biosimilars.
The implications of a biosimilar’s identifying suffix.
Their comfort levels when: a) prescribing to ‘treatment-naïve’ (new) patients; b) switching stable patients from an originator medicine to a biosimilar; c) prescribing a biosimilar with interchangeable status.
Their likelihood of prescribing: a) biosimilars with interchangeable status; and b) reference products for which biosimilars with interchangeable status are available.
If, when a biosimilar approved as interchangeable for one indication of its reference product, whether it should automatically be approved (through extrapolation) as interchangeable for all indications of the reference product.
The importance of having the authority to designate a biological medicine as ‘DISPENSE AS WRITTEN’ or ‘DO NOT SUBSTITUTE’, when: a) faced with a situation where substitution by a pharmacist; or b) faced with a situation where it is permissible for payer (public or private) to require a patient who is stable on their current biological to switch to a biosimilar.
The importance of: a) being notified by the pharmacist that a patient has received a biological other than the one prescribed, if the patient was receiving chronic (repeated) treatment; and b) having the sole authority to decide, together with patients, the most suitable biological medicine for their disease.
The acceptability of a pharmacist making the determination which biological (innovator or biosimilar) to dispense to a patient on initiation of treatment, if agreed in advance.
Their comfort levels: a) when switching patients to a biosimilar for non-medical reasons, i.e. cost or coverage; b) with a third party switching of a patient to a biosimilar for non-medical reasons, i.e. cost or coverage; and c) in situations where a payer requires a switch to be made for a patient who is stable on their current biological onto their preferred biological or biosimilar product.
The importance of: a) payers, such as health insurers and government agencies, having the formulary flexibility to reimburse multiple products in a particular class, including originator products and biosimilars; and b) payers, such as health insurers and government agencies, considering factors other than cost when determining coverage.
Whether scenario 10a or 10b would be better for patients: a) is when multiple products, including innovator and biosimilars are reimbursed, and biosimilars may be encouraged for new patients with no automatic substitution permitted; and b) is when only government chosen biosimilars are reimbursed and new patients must be prescribed this and current patients forced to switch.

All data refer only to those who completed the survey. All data were analysed in MS Excel and checked manually.

Results

Familiarity with biosimilars/confidence in their safety and efficacy
When carrying out the survey, participants were first given two explanatory texts to examine. These were:

Given immediately preceding Question 1:
Biological medicines are therapeutic proteins produced using living cells. The active substances of biological medicines are larger and more complex than those of non-biological medicines, i.e. ‘small molecule’ drugs. A biosimilar medicine is a biological medicine that is developed to be highly similar to an existing biological medicine (the ‘reference product’). To be approved by FDA, a biosimilar must demonstrate it has no clinically meaningful differences from an existing FDA-approved reference product in terms of safety, purity, and potency (safety and effectiveness).

Given immediately preceding Question 2:
FDA distinguishes biosimilars from older reference originator products by means of a unique four-letter suffix representing the biosimilar’s manufacturer. This suffix is appended to a non-proprietary name shared by the reference product and all its biosimilars, e.g. examplemab-xxxx, examplemab-yyyy. While older products have not been renamed, this is the same approach used for all newly approved biological products.

Question 1 considered the physicians’ confidence level regarding prescribing biosimilars and the majority (91.8%) said they were either highly or somewhat confident in doing this. The physicians that expressed most confidence (over 60.0% being highly confident) in prescribing biosimilars practiced in gastrointestinal, endocrinology and rheumatology.

Question 2 considered whether the use of an identifying suffix implies that a biosimilar is inferior to its reference product in terms of safety or efficacy, and most practitioners (72.8%) said that it did not. This was supported most by respiratory/pulmonology, endocrinology and infectious disease practitioners, with over 80.0% of each group stating that the suffix did not imply an inferior product. Note that FDA applies such suffixes not only to biosimilars but to all new biological products, while older reference products are not renamed with suffixes [17].

Prescribing and switching
The majority (89.0%) of physicians were either very or somewhat comfortable regarding prescribing a biosimilar to a ‘treatment-naïve’ (new) patient. Endocrinologists and gastrointestinal physicians were most comfortable, with over 60.0% of each group being very comfortable prescribing a biosimilar to a ‘treatment-naïve’ (new) patient.

Concerning how comfortable the physicians felt with switching a stable patient from an originator medicine to a biosimilar, 79.8% were either very or somewhat comfortable. Those that were most comfortable, with over 50.0% of practitioners in each group being very comfortable switching, were infectious disease, endocrinology oncology, and nephrology specialists.

Interchangeability
Prior to being asked about interchangeability, the participants were given the following text to examine:

The FDA recently granted the first ‘interchangeable’ designation to an insulin glargine biosimilar. This means the biosimilar’s manufacturer has provided additional data to FDA demonstrating that a patient repeatedly switched between the biosimilar and the originator can expect the same clinical results, without additional risks, as a patient who remained on the originator. Thus, it can be substituted at the pharmacy level without prior approval from the prescribing physician, unless he/she expressly prevents substitution when prescribing.

Then, when asked if they were more or less likely to prescribe a biosimilar carrying interchangeable status, 56.8% said they were much or somewhat more likely to prescribe it, whereas 36.4% said that the interchangeable designation would not affect their prescribing behaviour. Over 60.0% of those practicing infectious diseases, gastrointestinal, allergy/immunology, oncology and rheumatology were more or somewhat more likely to prescribe a biosimilar with interchangeable status. However, those practicing endocrinology, internal medicine, and urology were less likely to be affected by the interchangeable status, with over 40.0% of practitioners in each therapeutic specialty stating so, see Table 3.

Table 3

When asked about comfort levels with pharmacy substitution of a biosimilar with the interchangeable designation, 59.1% were somewhat or much more comfortable with this, whereas 33.2% said that the interchangeable designation would not affect how comfortable they felt about pharmacy substitution. 60.0% or more of those practicing allergy/immunology, gastrointestinal, internal medicine, infectious diseases, and oncology were much or somewhat more comfortable with pharmacy-level substitution of biosimilars with interchangeable status. The comfort level of those practicing endocrinology and rheumatology was less likely to be affected by the interchangeable status, with over 40.0% of practitioners in each therapeutic specialty stating so, see Table 4.

Table 4

When asked if, knowing that an interchangeable biosimilar may be automatically substituted, would the physicians be more or less likely to prescribe its reference product, 37.7% were somewhat or much more likely to prescribe it, whereas 50.9% said that the status would not affect the likelihood of them prescribing the reference product, see Figure 5, and 11.5% were somewhat or much less likely to prescribe the reference product. More physicians practicing gastrointestinal, internal medicine, nephrology, oncology, and rheumatology were much or somewhat more likely to prescribe the reference product, with over 40.0% of practitioners in each therapeutic specialty stating this. However, over 50.0% of those practicing dermatology, neurology and respiratory/pulmonology medicine stated that the interchangeable status would not affect the likelihood of them prescribing a reference product. And over 17.0% of those practicing infectious diseases and endocrinology were somewhat or much less likely to prescribe the reference of a biosimilar with interchangeable status.

With regard to automatic substitution, 43.6% of practitioners thought that, if a biosimilar is approved as interchangeable for one indication of its reference product, see Figure 5, it should automatically be approved (through extrapolation) as interchangeable for all indications of the reference product. The practitioners in the fields of endocrinology, gastrointestinal, and oncology, were most in favour of this, with 50.0% or more of practitioners in each field, believing that automatic substitution was appropriate.

Substitution and switching
When faced with a situation where substitution by a pharmacist is an option, 67.1% of practitioners thought it was critically or very important for them to have the authority to designate a biological medicine as ‘DISPENSE AS WRITTEN’ or ‘DO NOT SUBSTITUTE’, see Figure 6. The practitioners in the fields of dermatology, internal medicine and respiratory/pulmonology were most behind this, with over 70.0% of practitioners in these groups stating this authority was critically or very important.

When faced with a situation where it is permissible for payer (public or private) to require a patient who is stable on their current biological to switch to a biosimilar, 64.4% of practitioners thought it was critically or very important to have the authority to designate a biological medicine as ‘DISPENSE AS WRITTEN’ or ‘DO NOT SUBSTITUTE’, see Figure 6. The practitioners in the fields of dermatology and internal medicine were most behind this, with over 70.0% of practitioners stating this authority was critically or very important.

When asked about how important it would be for practitioners to be notified by the pharmacist that a patient has received a biological other than the one prescribed, if the patient was receiving chronic (repeated) treatment, see Figure 7, 71.0% said it was critically or very important. Dermatology practitioners were most concerned about this, with almost 85.0% stating it was critically or very important. On the other hand, infectious disease and endocrinology practitioners were least concerned about this, with a relatively large proportion (more than 20.0% of each group) stating it was only slightly important or not important.

The majority (67.8 %) of practitioners thought it was either totally acceptable or acceptable, if agreed in advance, for a pharmacist to determine which biological (innovator or biosimilar) to dispense to a patient on initiation of treatment. However, dermatologists were least in support of this, with 68.4 % of them stating this was not acceptable, see Table 8.

Table 8

The majority (68.5%) of practitioners stated that it was critically or very important for them to have the sole authority to decide, together with patients, the most suitable biological medicine for their disease. Dermatology, gastrointestinal and allergy/immunology practitioners were most behind this, with over 75.0% of each group stating it was critically or very important, see Figure 9.

Regarding switching patients to a biosimilar for non-medical reasons, i.e. cost or coverage, 77.8% of practitioners were very or somewhat comfortable with this idea, see Figure 9. Endocrinology, oncology, and rheumatology practitioners were most behind this, with over 80.0% of each group stating they were very or somewhat comfortable with switching for non-medical reasons. Dermatologists were most uncomfortable with this, with over 30.0% of the practitioners stating they were somewhat or very uncomfortable with switching for non-medical reasons.

Concerning third-party switching of a patient to a biosimilar for non-medical reasons, i.e. cost or coverage, 40.4% of practitioners stated they were very or somewhat comfortable with this idea. Endocrinologists were most comfortable with this, with over 25.0% of them being very comfortable with third party switching. Dermatologists were again least comfortable with this, with almost 85.0% of them being somewhat or very uncomfortable.

Of the physicians who were unsure about or uncomfortable with third-party switching of a patient to a biosimilar for non-medical reasons, they cited unknown immunogenicity reactions, potential symptoms return and legal liability as a physician, as their top three greatest concerns about non-medical switching to a biosimilar.

Summary

Over 70.0% of physicians thought it was critically or very important that payers, such as health insurers and government agencies, have the formulary flexibility to reimburse multiple products in a particular class, including originator products and biosimilars. Over 25.0% of gastrointestinal and allergy/immunology practitioners stated this was of critical importance.

Almost 75.0% of physicians thought it was critically or very important that payers, such as health insurers and government agencies, consider factors other than cost when determining coverage. Over 35.0% of gastrointestinal and neurology practitioners stated this was of critical importance.

The split was more even regarding comfort levels regarding situations where a payer requires a switch to be made for a patient who is stable on their current biological onto their preferred biological or biosimilar product, 45.9% were very or somewhat comfortable with this whereas 52.9% were somewhat or very uncomfortable with this. Those that were most comfortable with this were the endocrinologists and oncologists, with 60.0% and over being very or somewhat comfortable. Dermatologists were least comfortable with this, with over 80.0% being somewhat or very uncomfortable with a payer requiring a switch to be made for a patient who is stable on their current biological onto their preferred biological or biosimilar product.

The majority of physicians, over 80.0%, stated that a scenario where multiple products, including innovator and biosimilars are reimbursed, and biosimilars may be encouraged for new patients with no automatic substitution permitted, would be better for patients over a scenario where only government chosen biosimilars are reimbursed and new patients must be prescribed a biosimilar and current patients forced to switch.

Conclusion

The survey reveals information about these US physicians’ familiarity with biosimilars, how they feel about the interchangeable designation, and biological medicines switching choices made by them, pharmacists and payers.

Funding sources

The survey study was funded by the Alliance for Safe Biologic Medicines (ASBM) and administered by Industry Standard Research, LLC.

The activities of the ASBM are funded by its member partners who contribute to ASBM’s activities. Visit www.SafeBiologics.org for more information.

Authors

Michael S Reilly, Esq

Ralph D McKibbin, MD, FACP, FACG, AGAF
810 Valley View Boulevard, Altoona, PA 1660, USA

Competing interests: Dr Ralph D McKibbin is a gastroenterologist in active practice. He serves as chair of the executive committee for the Alliance for Safe Biologic Medicines for which he receives fair market compensation. He also serves pro bono in an advisory role for other organizations including the Pennsylvania Society of Gastroenterology, the American College of Gastroenterology, the Digestive Disease National Coalition, and the Dean’s Development Council of the Penn State Ross and Carol Nese College of Nursing. He provides disease state lectures for AbbVie and Bristol Meyer Squibb for fair market compensation.

Mr Michael S Reilly, Esq is the Executive Director and employed by Alliance for Safe Biologic Medicines. Mr Reilly served in the US Department of Health and Human Services from 2002 to 2008.

Provenance and peer review: Not commissioned; externally peer reviewed.

References
1. GaBI Online – Generics and Biosimilars Initiative. FDA approves its first biosimilar [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2022 Oct 17]. Available from: www.gabionline.net/Biosimilars/News/FDA-approves-its-first-biosimilar
2. U.S. Food and Drug Administration. Biosimilar product information [homepage on the Internet]. [cited 2022 Oct 17]. Available from: https://www.fda.gov/drugs/biosimilars/biosimilar-product-information
3. U.S. Food and Drug Administration. Guidance for industry. Scientific considerations in demonstrating biosimilarity to a reference product. April 2015 [homepage on the Internet]. [cited 2022 Oct 17]. Available from: www.fda.gov/regulatory-information/search-fda-guidance-documents/scientific-considerations-demonstrating-biosimilarity-reference-product
4. U.S. Food and Drug Administration. Considerations in demonstrating interchangeability with a reference product. Guidance for Industry. May 2019 [homepage on the Internet]. [cited 2022 Oct 17]. Available from: https://www.fda.gov/media/124907/download
5. Derbyshire M. USA and Europe differ in interchangeability of biosimilars. Generics and Biosimilars Initiative Journal (GaBI Journal). 2017;6(4):183-4. doi:10.5639/gabij.2017.0604.039
6. GaBI Online – Generics and Biosimilars Initiative. Interactive map for interchangeable biosimilars [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2022 Oct 17]. Available from: www.gabionline.net/biosimilars/general/interactive-map-for-interchangeable-biosimilars
7. GaBI Online – Generics and Biosimilars Initiative. FDA approves first interchangeable insulin glargine biosimilar [www.gabionline.net]. Mol, Belgium: Pro Pharma Communications International; [cited 2022 Oct 17]. Available from: www.gabionline.net/biosimilars/news/fda-approves-first-interchangeable-insulin-glargine-biosimilar
8. Drugs.Com. Cimerli FDA approval history [homepage on the Internet]. [cited Oct 17]. Available from: https://www.drugs.com/history/cimerli.html
9. U.S. Food and Drug Administration. FDA approves Cyltezo, the first interchangeable biosimilar to Humira [homepage on the Internet]. [cited Oct 17]. Available from: https://www.fda.gov/news-events/press-announcements/fda-approves-cyltezo-first-interchangeable-biosimilar-humira
10. Dolinar RO, Reilly MS. Biosimilars naming, label transparency and authority of choice – survey findings among European physicians. Generics and Biosimilars Initiative Journal (GaBI Journal). 2014;3(2):58-62. doi: 10.5639/gabij.2014.0302.018
11. European prescribers’ attitudes and beliefs on biologicals prescribing and automatic substitution. Generics and Biosimilars Initiative Journal (GaBI Journal). 2020;9(3):116-24. doi: 10.5639/gabij.2020.0903.020
12. A survey of Australian prescribers’ views on the naming and substitution of biologicals. Generics and Biosimilars Initiative Journal (GaBI Journal). 2017;6(3):107-13. doi: 10.5639/gabij.2017.0603.022
13. Biosimilars naming, label transparency and authority of choice – survey findings among European physicians. Generics and Biosimilars Initiative Journal (GaBI Journal). 2014;3(2):58-62. doi: 10.5639/gabij.2014.0302.018
14. Prescribing practices for biosimilars: questionnaire survey findings from physicians in Argentina, Brazil, Colombia and Mexico. Generics and Biosimilars Initiative Journal (GaBI Journal). 2015;4(4):161-6. doi: 10.5639/gabij.2015.0404.036
15. Naming and labelling of biologicals – a survey of US physicians’ perspectives. Generics and Biosimilars Initiative Journal (GaBI Journal). 2017;6(1):7-12. doi: 10.5639/gabij.2017.0601.003
16. Naming and labelling of biologicals – the perspective of hospital and retail pharmacists. Generics and Biosimilars Initiative Journal (GaBI Journal). 2016;5(4):151-5. doi: 10.5639/gabij.2016.0504.040
17. Nonproprietary naming of biological products: Update. Guidance for Industry. March 2019 [homepage on the Internet]. [cited Oct 17]. Available from: https://www.fda.gov/media/121316/download

Author for correspondence: Michael S Reilly, Esq, Executive Director, Alliance for Safe Biologic Medicines, PO Box 3691, Arlington, VA 22203, USA

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 23/08/2024

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On statistical evaluation for interchangeability of biosimilar products

Posted on August 1, 2022

Author byline as per print journal: Yuqi Li, BS Pharm; Shein-Chung Chow, PhD

Abstract:
A biosimilar product is a biological product which is highly similar to an existing reference product in structure and function and has no clinically meaningful difference in terms of safety, purity or potency. Under the Biologics Price Competition and Innovation Act of 2009 (BPCI Act), the Food and Drug Administration (FDA)-approved interchangeable biosimilar products can be expected to produce the same clinical result as the reference product in any given patient. In practice, although it is impossible to demonstrate that a proposed interchangeable biosimilar can meet this criterion due to differences in physiological conditions of patients and subtle differences between products, it is possible to demonstrate that the interchangeable biosimilar can produce the same clinical result as the reference product in any given patient with certain assurance. In this article, we derived a statistical method, which we refer to as an interchangeability index, for evaluating of the interchangeability of a biosimilar product with a certain statistical assurance. The proposed method was evaluated via extensive simulation studies. The results indicate that when the ratio of mean clinical results produced by test and reference product is within a narrow limit and the clinical results have only moderate variability, higher interchangeability index would suggest the test products are likely to meet the criteria for biosimilar interchangeability.

Submitted: 30 June 2022; Revised: 28 July 2022; Accepted: 29 July 2022; Published online first: 11 August 2022

Introduction

Biological products are typically large, complex, biologically active molecules produced by living systems, such as micro-organisms, plants or animal cells. These bioproducts are diverse and they may have preventive, diagnostic and therapeutic functions for diseases. Unlike chemical drugs made by non-biological, synthetic processes, biological products which are complex biomolecules, the manufacture of which produces some expected slight differences. Biological products are regulated by the US Food and Drug Administration (FDA), and the review and evaluation of manufacturing performed by FDA can help ensure that the produced biological products have consistent clinical performance [1]. Reference products are biological products approved by FDA based on extensive pre-clinical and clinical safety and efficacy data. A biosimilar product is defined as a biological product that is highly similar to an existing reference product in structure and function and has no clinical difference in terms of safety, purity or potency [1].

As an increasing number of biosimilars become available on the market, more drug use options are provided by introducing competition, the cost of treatment has been reduced. Thus, the medical treatments have become more accessible to patients. Given the availability of numerous options for drug use, it is natural to consider the issue of interchangeability between biosimilars. As indicated in the additional requirements by the Biologics Price Competition and Innovation Act of 2009 (BPCI Act) [2], a proposed biosimilar product which is considered to be an interchangeable biosimilar product for a reference product must satisfy two criteria. First, the biosimilar product can be expected to ‘produce the same clinical result as the reference product in any given patient’. Second, the risk regarding safety and reduced efficacy of switching or alternating between the reference and the interchangeable biosimilar product is not greater than the risk of using the reference product without switching or alternating. The demonstration of a proposed interchangeable biosimilar product is highly similar to a reference product in producing clinical results. In other words, the proposed biosimilar can meet the criteria, and a valid clinical trial design such as a crossover design must be conducted [3].

Considering the first criterion, in practice, it is impossible to demonstrate that a proposed interchangeable biosimilar product can produce the same clinical result as the reference product in any given patient. This could be due to various reasons, such as the fact that the underlying pathology and physiological conditions are not identical in each patient, and the fact that there are slight, acceptable within-product differences in the manufacturing process of the biological product from batch to batch. However, it is statistically possible to demonstrate that the interchangeable biosimilar can produce the same clinical result as the reference product in any given patient with certain assurance. Towards this goal, we mainly focused on the first criterion, and we proposed a statistical approach by evaluating the probability that reference and test products produce the same clinical results in any given patient. When this probability exceeds a prespecified threshold, we then claim that the biosimilar product is interchangeable.

In section 2, some rules regarding clinical data and basic study designs for switching/alternation in interchangeable biosimilar products are introduced. In section 3, statistical methods for estimating the proposed probability, which is referred to as an interchangeability index, are derived theoretically. In section 4, extensive simulation studies are performed to evaluate the proposed method. In section 5, conclusions are provided based on the methods and simulation study results.

Criteria and study design

Log-transformed data and therapeutic index limit
Given the clinical results are considered in related studies, pharmacokinetic data are typically collected usually to assess the interchangeability using statistical methods with some prespecified criteria. The raw pharmacokinetic data may often not be symmetrically or normally distributed, and a large range of the data may be noted. To address these issues and to make it easier to process the data for biostatistics analysis, FDA 1992 and 2001 guidance [4, 5] suggest considering the logarithmic transformation of pharmacokinetic data. Log-transformed data do not change the nature of the data or the correlations between variables. Rather, this transformation compressed the range of the data, making it easier to perform statistical analysis, and the effect of outliers is also reduced [5]. In practice, log-transformed pharmacokinetic data tend to have normal or approximately normal distributions, representing another important reason for the use of logarithmic transformation of data. The standard deviation of log-transformed data is often 1% of the standard deviation of the raw data. In addition, the logarithmic transformation could almost eliminate the problem of heteroskedasticity in the analysis.

Recall that our goal is to evaluate the probability that a biosimilar product produces the same clinical results in any given patient as a reference product. Although it is unlikely that the two products will produce identical clinical outcomes, the clinical results from the two products are probably within a narrow limit. Considering the ratio of the clinical outcomes, which are numeric data, if the clinical results are almost identical, the ratio should be close to 1. A limit of the therapeutic index can be set for the ratio. That is, if the ratio is within a narrow limit including 1, we may consider the two products as interchangeable. Since the log-transformed data are used in the analysis, the limit of the therapeutic index between the reference and biosimilar product should satisfy L₁ × L₂ = 1, thus there will be symmetric limits within the log-transformed space. Of course, given that biological products target a large population, in addition to the mean of clinical results, the variability due to subject-by-product should also be considered. We will discuss this information in later sections.

Switching design
As noted in the introduction, to determine whether a proposed biological product is an interchangeable biosimilar product, a valid clinical study design is necessary. FDA defines the switching as a single switch, whereas alternation is defined as multiple switches between two biological products, respectively [3]. An adequate design can be useful to evaluate whether a proposed biosimilar product can produce the same clinical result in any given patient as a reference product and evaluate the risk in terms of efficacy and safety with or without switching/alternation.

The FDA guidance about biosimilar interchangeability recommends a 2 × (m + 1) crossover design [3], where m is the number of switches. For a single switch, an adequate crossover design consists of two sequences which are RT and RR, where R represents the reference product and T represents the test product. This design is denoted by (RT, RR), which can evaluate the effect and safety of the switch from R to T and no switch. The relative risk of product use between the switch and no switch can also be assessed. When more than one switch occurs (m ≥ 2), a 2 × (m + 1) crossover design is still necessary. For example, when it switches twice (m = 2), a 2 × 3 crossover design consists of the two sequences which are RTR and RRR. This design is denoted by (RTR, RRR). This design is able to evaluate the efficacy of the switch from R to T and then to R and the efficacy of no switch. The relative risk can also be estimated under the study design.

In this case, in addition to the 2 × (m + 1) crossover design, a n-of-1 trial design has become an alternative popular design in recent years [6]. In a n-of-1 trial, a single subject is the entire trial. Random allocation is used to determine the order of the treatments given to a subject. This trial can be used to evaluate the difference in treatment effect within the same individual when multiple treatments are assigned at different periods. [7, 8] In fact, the n-of-1 trial has a nature of crossover design which can assess the relative risk between switching/alternation and without switching/alternation.

Statistical method

Interchangeability index
Without loss of generality, we assume that the data from clinical trials have been logarithmically transformed and follow a normal distribution with specified mean and variance. Let Y_R and Y_T be the clinical results of the reference product and the test product, where R = log Y_R and T = log Y_T follow normal distributions with means µ_R, µ_T and variances σ²_R, σ²_T, respectively. Referring to the idea of using P(X < Y) [9, 10] to assess the interchangeability between two biological products, we propose the following probability as an index to evaluate the consistency of the clinical results of the reference and test products:

Math 1

Where 0 < L₁ < 1 and L₂ > 1, L₁ and L₂ are defined as the acceptable lower bound and upper bound of the therapeutic index, respectively. Based on the characteristics of logarithm transformation, the limit of therapeutic index between the reference and biosimilar product should satisfy L₁ × L₂ = 1, then the transformed limits will have the same distance to 0 (after log-transformation, log 1 = 0 ). The proposed interchangeability index refers to the probability p. Denoting F as the ratio of Y_T and Y_R , as F converges to 1, p tends to 1. The probability p converging to 1 indicates that the two products can be considered as identical in terms of producing clinical results. The ratio F converging to 1 will require a high degree of clinical consistency between the two products for any given patient, which is usually diffi cult to realize in practice.

Estimate of interchangeability index
Under the normal distribution assumption of R = log Y_R and T = logY_T, where R ~ N (µ_R, σ²_R) and T ~ N (µ_T, σ²_T), the probability p can be derived as the form below:

Math 2

where Φ(z₀) = P (Z < z₀), Z is a standardized normal random variable. Thus, the interchangeability index p is a function of the parameters ^~θ = (µ_T, µ_R, σ²_T, σ²_R). Assuming that in a study design, the observations are presented by R_i = log Y_Ri, i = 1, …, n_R and T_i = log Y_Ti, i= 1, …, n_T. Then the maximum likelihood estimator (MLE) of the probability p can be derived as following:

Math 1

Based on the normality and large sample assumptions, there are still some asymptotic statistical results holding. Since the derived formula for the estimate of p is very complex, we consider using the Taylor expansion formula to approximate p locally. Recall that:

Math 2

Applying Taylor expansion of at p, in other words, at X = X_k = (μ_T, μ_R, σ²_T , σ²_R), we can get:

Math 3

Where H (X_k) is Hessian Matrix.

Math 4

We can further derive the first term of this Taylor expansion as the leading term. In addition, to simplify this case, we will only focus on the leading term in expectation, so that the expectation for can be rewritten as the following formula:

Math 6

Following the same idea, we can also get the variance of :

Math 7

To simplify these formulas, let E() = p + B(p) + O(n^–2), where B(p) is the leading term in the expectation formular mentioned above and is also the bias between and p. Since O(n^–2) is the reminder term, in statistics we can omit its effect. Similarly, let Var () = C(p) + O(n^–2), where C(p) is the leading term of Var ().

Since we assume the large sample in study, using Slutsky’s Theorem,

Math 8

In this situation, applying the expectation and variance derived above, we can furthermore derive that:

Math 9

where B() and C() are the estimates of B(P) and C(P). As the sample size increases to infinity, B(P) converges to 0 and then will be asymptotically unbiased.

Based on these theorems above, an approximate (1 – α) 100% confidence interval (CI) for the interchangeability index P) and C(P can be obtained. Since the proposed probability indicates to what extent the test and reference products are identical, in other words, interchangeable, in terms of producing clinical results in comparable population, we only focus on the lower bound of the confidence interval. Thus, we can construct a one-side (1 – α) 100% CI for interchangeability index P as following:

Math 10

Based on the data from a switching design, we can calculate , the point estimate, and L(), the lower bound of a one-sided (1 – α) 100% CI for the interchangeability index p. Given significance level α and a pre-specified threshold β, we can compare β and L(). If L() ≥ β, we could conclude that the test and reference biological products are interchangeable.

Simulation study

For a valid statistical analysis of biosimilar interchangeability, it is necessary to perform the statistical procedure under some prespecified acceptance criteria. We will construct a 95% CI for the proposed interchangeability index described previously. If the 95% CI lower bound is greater than a prespecified threshold β for interchangeability, we will claim that the test product is interchangeable for the reference product.

In this section, we will perform simulation studies to evaluate the performance of the proposed statistical method regarding interchangeability. We will specify different distribution parameters for the normal distribution to generate simulated experimental log-transformed pharmacokinetic data, perform statistical analysis on these data to calculate the interchangeability index and its one-sided 95% CI, and further explore the influence of the distribution parameters on the statistical results and threshold selection based on these simulations, and select the sample size for different data and thresholds.

First, we need to clarify some denotations and assumptions in this study:

(1) To provide a more specifi c context for the simulation study, we try to set concrete therapeutic index limits (L₁ and L₂). Considering L₁ × L₂ = 1, to make our simulation study more general without ﬁ rst setting a harsh criterion, in this case, we will propose L₁ = 0.8 and L₂ = 1.25.
(2) Let F = Y_T/Y_R, where Y_T and Y_R are the means of the clinical results produced by test and reference products, respectively. When F ∈ (0.8, 1.25) is in fact, it is possible that the two products could be claimed to be interchangeable.
(3) We will assume n_T = n_R= n in the switch design given that crossover trial designs typically enrol a similar number of comparable subjects for both sequences.
(4) We will assume σ_T = σ_R = σ given that the logarithmic transformation substantially reduces the variance of the data, so the variance of the transformed data should be approximately the same for pharmacokinetic data from comparable populations.

Average probability and the lower bound of 95% CI
Given the different ratios of Y_T and Y_R (ranging from 0.75 to 1.30) and different standard deviations of the log-transformed data which are normally distributed (ranging from 0.01 to 0.07). We chose the sample size n_T = n_R = 100. As mentioned in section 2.1, logarithmic transformation can reduce the standard deviation to approximately 1% of that of the raw data, thus we select this range of σ. In addition, regardless of the scale of the raw data, as long as the ratio of Y_T and Y_R is the same, this ratio will become the same difference after logarithmic transformation. Thus, the scale of the data has no effect on the results of the simulation study. The data were generated based on the prespecified parameters F and σ for 5,000 times, and the the average probability p (interchangeability index) and the lower bound of the 95% CI were calculated.

The results of simulation 1 are presented in Table 1.

Table 1

From the simulation results, we found that the interchangeability index decreases rapidly with increasing variance, meaning that a larger variance decreases the probability of two products being evaluated as interchangeable, even if the ratio of their means of clinical results is in the range of 0.8 to 1.25. It is reasonable because if a biological product produces a relatively large variance in clinical outcomes, it is an indication that it is not therapeutically stable and therefore will not be easily considered interchangeable.

Considering that σ = 0.07 expands one hundredfold to 7 as the standard deviation of the raw pharmacokinetic data, i.e., the coefficient of variation (CV) = 7%. This number represents a large variance and the lower bound of the CI is less than 90% for both cases with ratios of 0.9 and 1.1. Thus, we will not consider such a large standard deviation in subsequent simulation studies. For σ = 0.01, this standard deviation is so small that it means that the fluctuations in the data are minimal as long as the mean ratio of the clinical results produced by two products is within the range of 0.8 to 1.25 (not too close to the boundary). In addition, the interchangeability index is very high, and the test product is claimed to be interchangeable for the reference product. Thus, we will also not consider such a small standard deviation in further simulation studies.

Regardless of the chosen standard deviation, as long as the ratio F is outside the range of 0.8 to 1.25, the calculated interchangeability index is extremely small, indicating that such test products cannot generally be considered interchangeable under this statistical method. Thus, so we do not need to study the ratios outside the range of 0.8 to 1.25. In other words, this statistical method can well ensure that non-interchangeable products will not be claimed to be interchangeable. For the data in which the ratio is within the range from 0.9 to 1.1, as long as the standard deviation is not too large (e.g. σ = 0.07), the test products can be evaluated as interchangeable products for reference products under this statistical method. Thus, we do not need to continue to investigate the statistical results in this ratio range.

For further studies, we only need to focus on cases where the ratio F is between 0.8 and 0.9, 1.0 and 1.25, and only assume that the standard deviation of the log-transformed data is in the range of 0.3 to 0.5. Data with such characteristics are more meaningful for assessing the performance of this statistical method.

Changing the sample size
Based on the results of simulation 1, in this simulation we focused on statistics corresponding to variance and ratios in a specific range and evaluated the performance of our statistical method. Additionally, considering that the sample size affects the accuracy of the statistical results, this study sets different sample sizes for the calculation of the interchangeability index. Given that we expect the lower bound of the 95% CI of the interchangeability index to determine whether two products are interchangeable, we will only report the lower bound of the one-sided 95% CI in this study. Similarly, for each simulation, the process is performed 5,000 times. The chosen parameters and the results are presented in Table 2.

Table 2

Overall, given the variance and ratio, the interchangeability index almost still increases as the sample size increases within a certain range. When the sample size exceeds 100, the increase in the interchangeability index becomes unobvious. When the sample increases further, the value of the index almost just fluctuates without a significant increase. Therefore, considering that the switch design for biosimilar product interchangeability is usually a crossover design, a sample size of approximately 100 subjects for each sequence is appropriate based on the simulation results. Similar to the findings of simulation 1, the interchangeability index is lower when the ratio is close to 0.8 or 1.25. In general, this value cannot be increased significantly by increasing the sample size. According to the results of this simulation study, when the standard deviation is small (0.03), the interchangeability index has a relatively high probability of being greater than 80% if the ratio is in the range of 0.85–1.20. When the standard deviation is slightly larger (0.05), the interchangeability index can only reach a level of approximately 70% if the ratio is approximately 0.85 and 1.20. It is understandable that when the variance increases, the more the clinical outcomes produced by the biological product in patients fluctuate, the less likely it is to be assessed as interchangeable with the reference product.

Conclusion and discussion

For the assessment of drug interchangeability of biosimilar products, in practice, it is impossible to demonstrate that the test product can produce the same clinical therapeutic effect as that of the reference product given the difference in patients’ conditions and manufacturing differences and so on. In this article, we provided a statistical assurance that “test product has the same therapeutic effect as that of the reference product with certain assurance”. In other words, this statistical analysis assures a high probability that test product has the same therapeutic effect in any given patient, thus supporting the claim of interchangeability between test and reference products. For this purpose, following a similar idea of Chow et al. [10], a statistical method is proposed to estimate the probability of the two products producing the same clinical results (with an acceptable difference in a narrow limit).

In the simulation studies, we used 0.8 and 1.25 as the therapeutic index limits in reference to the 80/125 rule in bioequivalence for generic drugs. Indeed, the interchangeability of biosimilar products is not the same as bioequivalence of generic drugs, but similarities are noted to some extent. In practice, based on the definition of interchangeable biosimilar products, the limits might be narrower than 0.8 and 1.25. The simulation results indicate that for a ratio of two product means between 0.85 and 1.20, when the variance is not too large, the value of the interchangeability index can basically achieve 80% or greater with suitable sample size. That is, if we set an appropriate value to the threshold, the interchangeability index can be used to assess whether two biological products are interchangeable based on the data of the exchange design. However, it is difficult to claim that two products are interchangeable by calculating the interchangeability index when the clinical effects of the products fluctuate widely (large variance due to subjects by product) or when the ratio of the mean values of the two products is close to 0.8 or 1.25. For such a test product, the statistical method proposed in this study cannot yet be used as a valid evaluation tool, but this is an indicating the conservative nature of this statistical standard.

Further scenarios regarding this statistical method should be considered. Regardless of how we increase the sample size to the extent feasible in clinical trials, the value of the interchangeability index is well below 80% when the ratio is near 0.8 or 1.25. This finding is understandable. Consider a product tested has a mean clinical effect of 80% of the mean of the reference product, but the data fluctuate between patients. Here, the clinical effect produced in a large proportion of subjects will be less than 80% of the reference product. Thus, it is difficult for such a product to be recognized as interchangeable. The same is true when the ratio is approximately 1.25. For such a product, how exactly do we determine whether it is interchangeable with the reference product? This also requires further establishment of evaluation criteria based on its characteristics. In summary, the threshold for the interchangeability index and the therapeutic index limit are the main considerations when using this statistical method to claim whether a proposed biosimilar product is interchangeable for a reference product.

This interchangeability index is valid for the evaluation of biological products that meet certain conditions. However, the index in this study is only practical for switch design (a valid crossover design), and this article only addresses the first requirement for interchangeable biosimilar products according to the BPCI Act. The proposed method can be applied to switching design as recommended by FDA. To demonstrate biosimilar interchangeability, we also need to explore the relative risk between the test and reference products by performing study with a switch or alternation design. This requires further research under FDA’s recommended switching designs, either (RTR, RRR) for a single switch or (RTRT, RRRR) for multiple switching (alternation).

Competing interests:None.

Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Yuqi Li, BS Pharm, Master of Biostatistics candidate, BS Pharm
Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Suite 1102, Hock Plaza, 2424 Erwin Road, Durham, NC 27705, USA

Professor Shein-Chung Chow, PhD
Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Suite 1102, Hock Plaza, 2424 Erwin Road, Durham, NC 27705, USA

References
1. U.S. Food and Drug Administration. Guidance on scientific considerations in demonstrating biosimilarity to a reference product. April 2015 [homepage on the Internet]. [cited 2022 Jul 28]. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/scientific-
considerations-demonstrating-biosimilarity-reference-product
2. U.S. Food and Drug Administration. Biologic Price, Competition, and Innovation Act of 2009. 2009 [homepage on the Internet]. [cited 2022 Jul 28]. Available from: https://www.fda.gov/media/78946/download
3. U.S. Food and Drug Administration. Guidance for industry—considerations in demonstrating interchangeability with a reference product. 2019 [homepage on the Internet]. [cited 2022 Jul 28]. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-demonstrating-interchangeability-reference-product-guidance-industry
4. National Technical Reports Library. Guidance for Industry. Statistical approaches to establishing bioequivalence [homepage on the Internet]. [cited 2022 Jul 28]. Available from: https://ntrl.ntis.gov/NTRL/dashboard/searchResults/titleDetail/PB2010104191.xhtml
5. U.S. Food and Drug Administration. Guidance on statistical approaches to establishing bioequivalence. 2001 [homepage on the Internet]. [cited 2022 Jul 28]. Available from: https://www.fda.gov/regulatory-information/
search-fda-guidance-documents/statistical-approaches-establishing-bioequivalence
6. Chow SC, Song F, Cui C. On hybrid parallel–crossover designs for assessing drug interchangeability of biosimilar products. J Biopharm Stat. 2017;27(2):
265-71.
7. Lillie EO, Patay B, Diamant J, Issell B, Topol EJ, Schork NJ. The n-of-1 clinical trial: the ultimate strategy for individualizing medicine? Per Med. 2011;8(2):161-73.
8. Davidson KW, Cheung YK, McGinn T, Wang YC. Expanding the role of n-of-1 trials in the precision medicine era: action priorities and practical consideration. National Academy of Medicine. 2018. https://doi.org/10.31478/201812d
9. Jacobs R, Bekker AA, van der Voet H, Ter Braak CJF. Parametric estimation of P(X > Y) for normal distributions in the context of probabilistic environmental risk assessment. PeerJ. 2015;3:e1164.
10. Tse SK, Chang JY, Su WL, Chow SC, Hsiung C, Lu Q. Statistical quality control process for traditional Chinese medicine. J Biopharm Stat. 2006;16(6):861-74.

Author for correspondence: Yuqi Li, BS Pharm, Department of Biostatistics and Bioinformatics, Duke University School of Medicine, 2424 Erwin Road, Durham, NC 27705, USA

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 19/07/2024

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A case study of AstraZeneca’s omeprazole/esomeprazole chiral switch strategy

Posted on June 24, 2022

Author byline as per print journal: Federico J Piñeiro, Pharm, MPH; Fernández Argüelles Rogelio Alberto, Pharm, PhD

Introduction/Objective: To describe the chiral switch, an evergreening strategy used by AstraZeneca to position enantiopure esomeprazole as the new proton pump inhibitor market leader, displacing its predecessor omeprazole.
Methodology: A four-stage systematic review which included: a preliminary review, bibliographic review using databases, classification of the body of literature, and content analysis.
Results: Using different legal and commercial strategies, such as patent thickets and aggressive publicity campaigns, AstraZeneca transferred consumer loyalty from their successful omeprazole to esomeprazole, its new and more expensive patent protected product which has the same therapeutic value as its predecessor. This chiral switch allowed AstraZeneca to maintain monopoly prices, which increased the financial burden experienced by consumers and payors and may have also had a negative impact on access to the medication.
Conclusions: This case study exemplifies how the current patent system, including patent thickets, can be used to enhance the profits of pharmaceutical companies while stalling innovation and placing undue financial burdens on the consumer.

Submitted: 18 December 2021; Revised: 2 May 2022; Accepted: 6 May 2022; Published online first: 20 May 2022

Introduction/Objective

The 20th century witnessed extraordinary medical advances that have eradicated or controlled epidemics across the world and have lessened the impact of life-threatening diseases. Undeniably, the widespread use of pharmaceuticals has contributed to the sustained increase in life expectancy observed throughout this period. The pharmaceutical industry’s investments in research and development (R & D) have resulted in major contributions to our therapeutic arsenal. However, since Arnold Relman published ‘The new medical-industrial complex’ [1], significant changes in the business model adopted by the major pharmaceutical companies (from now on ‘Big Pharma companies’) have been observed [2].

Under the new paradigm, these companies, which trade in the stock market and must respond to the interests of the stockholders, no longer prioritize the development of drugs that would add high therapeutic value, but rather those that would maximize their profits [3]. To achieve this goal, in the context of the emergence of generic drugs in the late 1980s and 1990s, Big Pharma started focusing on maintaining the high prices facilitated by monopolies and worked on extending the commercial exclusivity of brand-name drugs. In other words, the industry maximized profits by using incentives intended to reward innovation to instead maximize their profits. These are outlined in Table 1 and include the protection of intellectual property through patents and data exclusivity.

Table 1

The term ‘evergreening’ refers to the use of legal, commercial and technological strategies to extend due-to-expire patents of successful products [6-8]. Big Pharma companies have used evergreening to prolong their legal monopoly, enabling the patent owner to maintain high prices and avoid losing the commercial benefits that would likely result from the commercialization of generic versions of their branded products [9, 10].

To shield the power of their monopoly, Big Pharma companies use evergreening and other strategies, such as taking advantage of aspects of legislation, to delay the entry of generics. For example, in the United States (US), the Hatch-Waxman act, extends the market exclusivity period of a new drug by six months when clinical trials are carried out in a paediatric population [11, 12], even if that drug does not treat a medical condition that occurs in paediatric patients.

Moreover, many Big Pharma companies have been increasingly developing drugs that are very similar to their original products (the so-called ‘me-too or follow-on drugs’). These are then launched just before the expiration of the patent on their original drug. When these drugs are released into the market, they are intensively promoted as being more advantageous than predecessors [7, 12, 13]. These new drugs can be developed using different shunting maneuvers, see Table 2, including the following: commercializing the active enantiomer of a drug already on the market (this ‘chiral switch’ strategy is described in detail below), modifying the formulation of the active pharmaceutical ingredient (API), using the active metabolite of a previously commercialized product, and combining more than one API in the same presentation.

Table 2

Most drugs that contain a chiral centre are marketed as racemic mixtures, that is, a combination of the two possible enantiomers. Usually, these two ‘halves’ have similar clinical activity and adverse effects; however, sometimes a pure enantiomer – also called enantiopure – may offer some therapeutic advantages. The market launch of an enantiopure product just before the patent expiration of its racemic predecessor has been described as a ‘chiral switch’ strategy, and often the new product does not offer any clinical advantages to justify the change [13, 14].

A relevant example of a chiral switch is the case of AstraZeneca’s omeprazole/esomeprazole. In 2000, omeprazole the lead proton-pump inhibitor (PPI), was the world’s bestseller, with annual US sales of US$6 billion a year, under the brand name Prilosec [15]. However, by 2010, enantiopure esomeprazole (sold as Nexium) became AstraZenca’s bestseller with US sales of US$5.63 billion, compensating for the plummeting of omeprazole [16]. According to Coherent Market Insights, in 2020 the estimated value of the global PPI market was US$2.9 billion and it was expected that its compound annual growth rate (CAGR) would be 4.30% during 2020–2027. The success in launching esomeprazole allowed AstraZeneca to maintain its leadership in the PPI market.

The objective of this article is to describe the omeprazole/esomeprazole chiral switch used by AstraZeneca as a case study that exemplifies the behaviours of the pharmaceutical industry. More specifically, we will analyse the published literature on the clinical evidence of esomeprazole’s therapeutic value and how AstraZeneca took advantage of regulations and pricing mechanisms to position enantiopure esomeprazole into a dominant market position.

Methodology

A qualitative systematic review was carried out in four stages. Initially, in the exploratory stage, the pre-existing knowledge and the theoretical framework were outlined. Subsequently, a literature search was carried out, using the digital databases: Scientific Electronic Library Online (SciELO), Scopus, Virtual Health Library (VHL), Sistema de Información Esencial en Terapéutica y Salud (SIETES) and PubMed. The goal was to generate a representative body of literature covering a wide geographic range and incorporating different approaches and opinions.

All searches, except SIETES, were done in English, using the terms: ‘blockbuster’, ‘pharmaceutical industry’, ‘esomeprazole’, ‘omeprazole’, ‘big pharma’, ‘patents’ and ‘evergreening’. In SIETES, due to the modality of this database, the search was carried out using the following Spanish keywords: ‘esomeprazol’, ‘patentes’, ‘enantiomeros’ and ‘industria farmacéutica’. Table 3 includes more details on the bibliographic search and the absolute number of articles identified through each search engine. Only peer-reviewed, scientific articles written in English, Spanish or Portuguese were included.

Table 3

The references of all the included articles were reviewed to identify additional references and other technical reports suggested by experts were incorporated into the analysis. After removing duplicate articles and those that did not meet the inclusion criteria, 32 of the 167 articles that had been identified were selected for analysis.

In the third stage, the body of articles were classified using content analysis techniques, particularly thematic analysis [17].

Results

Thirty-two articles were included in the final analysis and these were mostly written by researchers from Europe, the US and Australia. The information contained in the articles was classified into three different categories: clinical, regulatory and commercial.

Clinical aspects
Esomeprazole, the S-isomer of omeprazole, was launched in the US market by AstraZeneca, under the name Nexium^® in 2001, a few months before the expiration of patent of omeprazole (Prilosec^®). The loss of the omeprazole patent threatened the financial position of the company as it was their global bestseller [1, 15].

Given that omeprazole and esomeprazole have the same chemical structure and do not present pharmacodynamic differences, the company justified the development of the enantiopure exclusively on pharmacokinetic differences, particularly a difference in the affinity for CYP2C19, an enzyme belonging to the large hepatic enzyme complex of cytochrome P450, whose basic function is to transform its substrates into more polar and soluble molecules, thus facilitating their excretion. This would result in esomeprazole remaining active for a longer period than omeprazole [6].

In terms of published evidence, several studies [14, 18–20] have shown that the pivotal clinical trials of esomeprazole compared its efficacy against omeprazole at non-equipotent doses, and some trials used placebo as a comparator. Likewise, not all the results were favourable for the new enantiomer, and two articles [14, 18] unveiled the presence of publication bias. While the articles that showed the advantages of the new drug were published in the same year as its market approval, the studies that did not show a significant difference between the two drugs were published five years after approval when the new drug had already established itself as the best option to treat heartburn.

Regulatory aspects
Given the commercial importance of omeprazole, AstraZeneca deployed a wide variety of regulatory strategies to maintain its monopoly, as discussed in the following paragraphs.

Secondary patents: there are two types of patents; primary patents, which protect new chemical or biological compounds intended for therapeutic use in humans; and secondary patents, which protect non-essential aspects of the new molecule, such as small chemical variants, different crystalline conformations of the original compound, methods of use, new formulations and new dosage forms [8, 21].

A 2010 analysis of the Food and Drug Administration (FDA) website found that, in the US, omeprazole was protected by a total of 40 patents [22], constituting a ‘patent thicket’. Another example of such a thicket is highlighted in an article on the Australian market [23] which asserts that, in addition to the original patent for omeprazole, there were 61 additional patents, two of which clearly appear to have prevented generics from entering the market. Initially, an enteric-coated formulation, developed to delay the absorption of the active principle, precluded the commercialization of generics between 1999 and 2006, a period during which a new patent was introduced for the enantiomer esomeprazole [23, 24]. Taking the exclusivity period granted for the new product into account, the effective market monopoly of these two drugs (omeprazole and esomeprazole) in Australia exceeds 29 years [23].

Litigation for patent usurpation: Patent thickets are often used by Big Pharma to enable them to sue generic companies that attempt to enter the market; the greater the number of patents, the easier it is for Big Pharma to claim that one of them has been violated. The litigation process allows Big Pharma companies to extend their commercial exclusivity by the period noted in the legislation. For example, in the US, FDA-approved drugs and all their patents are included in the so-called ‘Orange-Book’, and when a generics manufacturer wants to market a generic of a brand-name drug it must submit an abbreviated new drug application (ANDA) to FDA. In addition, to ensure that no patent is being infringed, the generics manufacturer must certify one of the following:

i) the drug has not been patented
ii) the patent has already expired
iii) the generic drug will not enter the market until the patent expires
iv) the patent is invalid or will not be infringed by the generic drug.

If the fourth option is chosen (called ‘paragraph IV certification’), a notice must be sent immediately to the patent holder, who will have 45 days to take the case to court on the basis that the generic drug infringes a patent listed in the Orange Book. If the branded drug producer decides to litigate, the generic drug approval will automatically be delayed for 30 months or until the dispute is resolved or the patent expires, whichever occurs first [18].

Generics manufacturers, who are generally smaller and have fewer financial resources, are often discouraged by the high costs of the legal process. They face the dilemma of having to choose between entering the legal dispute, assuming the costs and the risk of an unfavourable resolution, or simply postpone their market entry until being absolutely sure that both primary and secondary patents have expired.

Paediatric clinical trials: Using federal regulations, AstraZeneca conducted paediatric clinical trials with omeprazole in the US, obtaining an additional six months of market exclusivity [1, 18].

Switching prescription drugs to over-the-counter (OTC): According to Kakkar (2015), AstraZeneca imposed a ‘double switch’ in the US: the chiral switch of Nexium, and the subsequent switch of Prilosec from prescription to OTC, shortly afterwards. Another article reports the use of the same strategy in Sweden, where, in 1999, the company also requested the change of omeprazole from a prescription to an OTC drug [25].

Commercial aspects
Several authors agree that AstraZeneca’s chiral switch was accompanied by an aggressive publicity campaign to encourage loyal consumers of the original racemic mixture to use the new patent-protected enantiopure product [26, 27]. In the US alone, it invested US$500 million, in direct advertising to the consumer, medical samples and discounts offered to hospitals when using the new drug [18, 28]. The US advertising campaign appears to have been successful as, shown in Figure 1, shortly after launching Nexium, its sales exceeded those of its predecessor.

Another article analysed the PPI market in Australia and highlighted that in 2003, of all prescriptions for the omeprazole/esomeprazole binomial, only 18% were for the new drug, while omeprazole retained the remaining 82%. By 2014, this proportion was inverted, and esomeprazole accounted for 77%, while omeprazole only held 23% [23].

A 2013 study [6] of the US market calculated the price difference between an equipotent dose of these two drugs for six weeks of treatment and found that patients using esomeprazole spent US$111 more that those using omeprozale. It is estimated in just a year, AstraZeneca generated an additional US$1.5 million from this chiral switch. Another article claims that 40% of patients in the US had switched to the new drug in 2003, and that change represented company earnings of US$3 billion during that year, and at least US$5 billion in 2004 [29]. In 2009, in England, the National Health Service (NHS) spent £42 million on esomeprazole at the primary healthcare level, despite the fact that it offers no clinical advantages and is 11 times more expensive than other available PPIs [30]. Similarly, an article that studied the costs associated with eight ‘follow-on drugs’ in Geneva, Switzerland found that the most prescribed was esomeprazole (55% of the total), which represented an additional cost of €5.2 million over the cost of using generic omeprazole during the period studied (2000‒2008) [31].

In 2003 in Australia, shortly after its approval, the price of esomeprazole was 118% that of omeprazole. This continued to increase and, in 2014, it had become 200% more expensive [23], see Figure 2.

Discussion

The results show the success of the strategies used by AstraZeneca to switch consumer loyalty from the successful omeprazole to the new esomeprazole, which allowed the company to maintain high monopoly prices. This case study also highlights the inability of the current intellectual property protection system to guarantee universal access to pharmaceuticals at affordable prices. This failure is reflected in the three interrelated issues that are discussed below.

Patent thickets
The patent system was designed so that, after a period of exclusivity, competing companies could develop and market the same product, engendering competition and leading to lower prices, while the period of intellectual property protection would serve as an incentive for Big Pharma to continue to invest in R & D [32]. However, in the case of pharmaceutical products, the reality is usually quite far from this theoretical model.

Patent authorities often award patents for trivial changes, and Big Pharma companies are using this to their advantage and often succeed in avoiding the commercial losses that would ensue from the presence of competing generics. In some European countries, the price of generics could be as low as 2% to 4% of the originator’s price before patent expiration [33], therefore, most innovative companies stand to lose a large share of their markets with the introduction of generics and therefore use a combination of strategies to maintain profits. In relation to this, a recent article points out that in the US, the popular etanercept is still under patent protection 37 years after its first patent was issued and 17 years after the main patent expired [32]. These patent thickets enable companies to maintain their market exclusivity, set high prices, and even expand their market share.

In the last two decades, the patent thicket practice has become widespread. Feldman (2018) shows that according to FDA’s records, between 2005 and 2015, 78% of the new patents were not issued for newly developed chemical compounds, but for changes made to some characteristics and/or manufacturing processes of drugs that were already in the market. Moreover, in the US, the ratio between secondary patents and primary patents has recently reached 7 to 1 [33]. These low-quality patents have been questioned in various countries because they might not meet patentability requirements (novelty, non-obviousness and industrial applicability), and have led to an increase in the litigation of intellectual property infringements [34]. The trick consists of protecting the original products with multiple patents to increase the possibilities that the release of a generic version might infringe a patent, lead to litigation and delay the presence of competing products.

This would not be a serious problem if it were not closely related to the fact that the low level of required inventiveness to grant patents, discourages real innovation while maintaining monopoly prices.

In the case of AstraZeneca’s chiral switch, the company wanted to maintain its leadership in the PPI market, so is not surprising that it was willing to use anti-competitive tactics, for which it has subsequently had to pay fines and defend its patents in court [15, 35].

Lack of innovation
If companies can extend their commercial monopolies without the need to strive for true innovation, it is not surprising that most newly commercialized drugs offer few additional benefits over older medicines. The increasing interest in enantiopure drugs seems to come in response to this way of thinking. Using data from the independent French publication Prescrire as a reference, of the 92 new products and indications that were approved in 2016, only 15 (or 16%) represented a possible therapeutic advance. These data do not appear to be exclusive to 2016 as the number of true innovative products has not changed much in the last 10 years [36].

Big Pharma’s R & D is focused on resolving problems that affect a large number of patients who can pay for drugs [1]. So, the lack of innovation is even more pronounced for diseases that affect fewer people and these become neglected. Only 4% of the drugs approved by FDA and the European Medicines Agency (EMA) between 2000 and 2011 were intended for the treatment of such pathologies [37]. Given that most of these neglected diseases are concentrated in developing countries [38], it is reasonable to think that the responses that Big Pharma is offering to these countries is even less satisfactory.

High prices
Although patients’ access to drugs depends on various factors, price is undoubtedly a key factor and high prices are a major public concern that threaten the medium-term viability of the health systems.

It should be noted that, according to the innovative pharmaceutical industry, prices do not only reflect the cost of raw materials, manufacturing and advertising of the approved product, but also the investment in R & D of products that have failed. However, the lack of transparency in Big Pharma’s expenditures precludes observers from verifying if the prices are linked to reasonable expenditures on each of these components [39]. Critics have suggested that these industries engage in other behaviours that lead to excessive pricing, such as providing high returns to investors, offering attractive compensation packages for senior executives, paying fines due to regulatory violations, extensive lobbying activities, and being involved in mergers and acquisitions above market value [40–42].

Published data show that governments, health insurers and patients in the US, Europe and Australia increased their expenditures on PPIs after esomeprazole became available in those countries.

Moir’s results (2016) appear to support the use of ‘shadow pricing’, a concept proposed by Angell [1], referring to the fact that companies usually set the price of a new drug in a range very similar to that of its predecessor (or in some cases, lower), in order to favour the transition to the new drug. Subsequently, once various generic drugs have entered the market, competition usually reduces the price of the original drug, increasing the price gap with the successor that is still under patent.

The problem with high prices is that many populations are left behind and without access to life-saving drugs. It is widely demonstrated in the literature [43, 44] that commercialization of generics promotes competition and lowers prices. In the case presented, an aggressive marketing campaign and patent thickets allowed a monopoly to be extended, which was detrimental to patients’ interests.

Together, these strategies have many consequences for patients, insurance companies and healthcare institutions. This manuscript has attempted to shed light on the problem and to encourage the implementation of independent cost-effectiveness studies. The comparison of all available therapeutic options could lead to better treatment choices, better health outcomes and the improved use of available resources.

Strengths and limitations
This manuscript’s main strength is that it has systematically and qualitatively evaluated the published literature surrounding AstraZeneca’s chiral switch omeprazole/esomeprazole. It has also systematically scrutinized the strategies used by AstraZeneca to extend its commercial monopoly in different countries.

The manuscript also has some limitations, being a qualitative systematic review, the use of search terms and the selection of articles is always affected by the subjective decision of the authors. Therefore, although the choice of databases and search terms was aimed at generating a representative body of literature, some relevant articles may have been omitted. Furthermore, the inclusion of additional chiral switch case studies could yield additional information on how new enantiopure substances have entered the market, in some cases such products may have provided clinical benefits to patients.

Conclusion

AstraZeneca’s omeprazole/esomeprazole chiral switch evergreening strategy was used to extend the commercial exclusivity of their blockbuster drug product. They introduced the enantiopure esomeprazole to the market as a new product, although it had no clinical advantages over its predecessor, omeprazole. As mentioned previously, this case was chosen due to the size of the PPI market and because it exemplifies the way in which the company deployed different strategies to prolong commercial exclusivity and increase its profits. This led to an increase in drug spending, both for individuals and for the public health systems.

Our continued reliance on Big Pharma companies for drug R & D and production has resulted in markets flooded with products with little or no utility, that often do not respond to the actual needs of the population.

This study has outlined three major problems that have resulted from the failures of the patent system and how they are closely related. The case of omeprazole/esomeprazole is paradigmatic; it shows that Big Pharma’s main goal is no longer the development of drugs with therapeutic value, but one of pseudo-innovation to maintain commercial monopolies for extended periods. This business model aims at maximizing profitability and not at preventing or curing diseases. Unless changes are promoted in the institutions responsible for guaranteeing intellectual property protections in the different countries, the granting of low-quality patents will continue to result in prolonging monopolies and discouraging true therapeutic innovation.

The study highlights that the current patent system is inefficient and does not work to benefit patients. It is therefore imperative to strengthen knowledge and competence at all levels of the healthcare systems to enhance the use of the most cost-effective medical options. It is also important to promote mechanisms to orient the R & D of the pharmaceutical sector towards medicines that respond to the health needs of the population and not to the interests of Big Pharma. Alternative models are being proposed, including public R & D, innovation prizes, and governmental investments in new products that are later sold by private companies with a reasonable profit margin. It is important to invest in exploring these and other alternative paths, to improve access to medicines in all regions of the world and prevent access to medicines being a privilege only for the few.

Summary paragraph: The authors believe the information contained in this manuscript may be relevant for prescribers, patients and the community in general. All of them will benefit from learning about the strategies used by the pharmaceutical industry that lead to increased prices for prescription drugs.

Acknowledgements

We would like to express our very great appreciation to Nuria Homedes, for her valuable and constructive suggestions to improve this research work.

Competing interests: The authors declare that there is no conflict of interest. This work has been carried out thanks to a CONICET (Argentina) scholarship.
Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Federico J Piñeiro, Pharm, MPH
Instituto de Salud Colectiva, Universidad Nacional de Lanús, 309 Thames, 1414 Buenos Aires, Argentina

Fernández Argüelles Rogelio Alberto, Pharm, PhD
Universidad Autónoma de Nayarit, 56 Shangay, Colonia Insurgentes, 63183 Tepic. Nayarit, México

References
1. Relman AS. The new medical-industrial complex.N Engl J Med. 1980;303(17): 963-70.
2. Angell M, Freire L. La verdad acerca de la industria farmacéutica cómo nos engaña y qué hacer al respecto. Bogotá: Grupo Editorial Norma; 2006.
3. Ugalde A, Homedes N. Medicamentos para lucrar. La transformación de la industria farmacéutica. Salud Colectiva. 2009;5(3):305-22.
4. Allard Soto R. Medicamentos esenciales y acuerdo sobre los ADPIC: colisión entre el derecho a la salud y el derecho de propiedad intelectual. Salud Colectiva. 2015;11(1):9-21.
5. Musungu SF, Villanueva S, Blasetti R. Utilizing TRIPS flexibilities for public health protection through South-South regional frameworks. 2004. CiteSeerX. [homepage on the Internet]. [cited 2022 May 2]. Available from: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.297.6970&rep=rep1&type=pdf
6. Lehmann DF, Wojnowicz S. The evergreening of biopharmaceuticals: time to defoliate. J Clin Pharmacol. 2016;56(4):383-9.
7. Feldman R. May your drug price be evergreen. J Law Biosci. 2018;5(3):590-647.
8. Collier R. Drug patents: the evergreening problem. CMAJ. 2013;185(9):E385-6.
9. Kesselheim AS. Rising health care costs and life-cycle management in the pharmaceutical market. PLoS Med. 2013;10(6):e1001461.
10. Kesselheim AS, Avorn J, Sarpatwari A. The high cost of prescription drugs in the United States: origins and prospects for reform. JAMA. 2016;316(8):858-71.
11. Darrow JJ, Avorn J, Kesselheim AS. FDA approval and regulation of pharmaceuticals, 1983-2018. JAMA. 2020;323(2):164-76.
12. Christie AF, Dent C, McIntyre P, Wilson L, Studdert DM. Patents associated with high-cost drugs in Australia. PLoS One. 2013;8(4):e60812.
13. Kakkar AK. Patent cliff mitigation strategies: giving new life to blockbusters. Expert Opin Ther Pat. 2015;25(12):1353-9.
14. Gellad WF, Choi P, Mizah M, Good CB, Kesselheim AS. Assessing the chiral switch: approval and use of single-enantiomer drugs, 2001 to 2011. Am J Manag Care. 2014;20(3):e90-7.
15. Hawkes N. AstraZeneca must pay €52.5m fine for anticompetitive tactics, rules European court. BMJ. 2012;345:e8396.
16. Lindsley CW. The top prescription drugs of 2012 globally: biologics dominate, but small molecule CNS drugs hold on to top spots. ACS Chem Neurosci. 2013;4(6):905-7.
17. Souza Minayo ME. La artesanía de la investigación cualitativa. 1°. Buenos Aires: 2013.
18. Dwivedi G, Hallihosur S, Rangan L. Evergreening: a deceptive device in patent rights. Technol Soc. 2010;32(4):324-30.
19. Gilhooley M. Heal the damage: prescription drug consumer advertisements and relative choices. J Health Law. 2005;38(1):1-44.
20. Shivashankar M, Mani D, Mandal BK. An overview on intellecual property rights in pharmaceutical and biotechnology industries. J Chem Pharm Res. 2011;3(2):753-61.
21. Organización Mundial de la Propiedad Intelectual. Resumen del estudio sobre patentes farmacéuticas en Chile. 2015 [homepage on the Internet]. [cited 2022 May 2]. Available from: https://www.wipo.int/edocs/mdocs/mdocs/es/cdip_15/cdip_15_inf_2.pdf
22. Lourenço AL, Lira LM, Carvalho DP de, Melo P de A, Cláudio-da-Silva TS. Gestão das inovações incrementais, o caso Omeprazola. Química Nova. 2010;33(4):1000-4.
23. Moir H. Exploring evergreening: insights from two medicines. Aust Econ Rev. 2016;49(4):413-31.
24. Lloyd M. Evergreening by whom? A review of secondary patents for omeprazole. Pharm Pat Anal. 2013;2(6):737-43.
25. Cohen JP, Paquette C, Cairns CP. Switching prescription drugs to over the counter. BMJ. 2005;330(7481):39-41.
26. Kyle GJ, Nissen LM, Tett SE. The Australian rise of esomeprazole-was expenditure on samples a contributor? Pharmacoepidemiol Drug Saf. 2009; 18(1):62-8.
27. Somogyi AA, Bochner F, Foster D. Inside the isomers: the tale of chiral switches. Aust Prescr. 2004;27(2):47-49+51.
28. Hess J, Litalien S. Battle for the market: branded drug companies’ secret weapons generic drug makers must know. J Generic Med. 2005;3(1):20-9.
29. Dutfield G. Healthcare innovation and patent law’s ‘pharmaceutical privilege’: Is there a pharmaceutical privilege? And if so, should we remove it? Health Econ Policy Law. 2017;12(4):453-70.
30. Hughes DA, Ferner RE. New drugs for old: disinvestment and NICE. BMJ. 2010;340:c572.
31. Vernaz N, Haller G, Girardin F, Huttner B, Combescure C, Dayer P, et al. Patented drug extension strategies on healthcare spending: a cost-evaluation analysis. PLoS Med. 2013;10(6):e1001460.
32. Gardner J. A three-decade monopoly: how Amgen built a patent thicket around its top-selling drug. Biopharma Dive. 2021 November 1.
33. Song CH, Han J-W. Patent cliff and strategic switch: exploring strategic design possibilities in the pharmaceutical industry. SpringerPlus. 2016;5(1):692.
34. Martínez Pérez M. Las patentes sobre “second generation products” utilizadas como estrategia para dilatar la entrada de genéricos en el mercado de la Unión Europea. Cuadernos de Derecho Transnacional. 2014;6(2):175-200.
35. Owens J. EC fines AstraZeneca in Losec antitrust case. Nat Rev Drug Discov. 2005;4(7):530.
36. New products and new indications in 2016: a system that favours imitation over the pursuit of real progress. Prescrire Int. 2017;26(182):136-9.
37. Pedrique B, Strub-Wourgaft N, Some C, Olliaro P, Trouiller P, Ford N, et al. The drug and vaccine landscape for neglected diseases (2000–11): a systematic assessment. Lancet Glob Health. 2013;1(6):e371-9.
38. Kindhauser MK. Communicable diseases 2002. Global defence against the infectious disease threat. Geneve: World Health Organization; 2003.
39. Perehudoff K, Mara K, ‘t Hoen E. What is the evidence on legal measures to improve the transparency of markets for medicines, vaccines and other health products (World Health Assembly resolution WHA72.8)? Copenhagen: WHO Regional Office for Europe; 2021. PMID: 34351727.
40. Light DW, Warburton R. Demythologizing the high costs of pharmaceutical research. BioSocieties. 2011;1:34-50.
41. Drug research: public funding, private profits. Prescrire International. 2020; 29(221):303-6.
42. Brown D, Hanna TH. It’s time for a public option in the pharmaceutical industry. In TheseTimes. 11 May 2018. [cited 2022 May 2]. Available from: https://inthesetimes.com/article/pharmaceutical-industry-drug-prices-trump-public-option
43. Simoens S. A review of generic medicine pricing in Europe. Generics and Biosimilars Initiative Journal (GaBI Journal). 2012;1(1):8-12. doi:10.5639/gabij.2012.0101.004
44. U.S. Food and Drug Administration. Generic competition and drug prices: new evidence linking greater generic competition and lower generic drug prices. 2019 [homepage on the Internet]. [cited 2022 May 2]. Available from: https://www.fda.gov/media/133509/download

Author for correspondence: Federico J Piñeiro, Pharm, MPH, Instituto de Salud Colectiva, Universidad Nacional de Lanús, 309 Thames, 1414 Buenos Aires, Argentina

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 19/07/2024

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Extended stability of the trastuzumab biosimilar ABP 980 (KANJINTI™) in polyolefin bags and elastomeric devices

Posted on September 29, 2021

Author byline as per print journal: Lyndsay Davies¹, PhD; Katie Milligan¹, BSc; Mark Corris¹, BSc; Ian Clarke¹; Paul Dwyer¹, MSc; Sarah Elizabeth Lee², PhD; Jolene Teraoka³, BSc; Jill Crouse-Zeineddini³, PhD; Jane Hippenmeyer⁴, PharmD

Study Objectives: To investigate the quality and in-use stability of the trastuzumab biosimilar ABP 980 (KANJINTI™) in both concentrated multi-dose bags and following dilution and extended storage in intravenous (IV) bags and elastomeric devices, to address the stability requirements of different global pharmacy practices.
Methods: The effect of extended refrigerated storage plus exposure to in-use temperature conditions on KANJINTI™ (trastuzumab) solutions was assessed using a range of stability-indicating analytical methods, including appearance, pH, SEC, non-reducing CGE, reducing-CGE, CZE, sub-visible particle counting and potency by a cell-based proliferation inhibition assay. Stability of reconstituted 21 mg/mL solution stored in multi-dose bags and diluted samples at 0.3 mg/mL, 0.8 mg/mL and 4 mg/mL in 0.9% w/v NaCl solutions stored in IV bags and elastomeric devices was determined over different storage durations. Forced degraded samples exposed to room temperature and natural daylight were used to demonstrate the stability-indicating abilities of the methods.
Results: No significant changes were observed in the appearance, pH, monomer concentration, purity, charge heterogeneity, sub-visible particle counts or bioactivity, regardless of initial concentration, container or storage duration.
Discussion: There was no indication of significant changes to the physicochemical stability or bioactivity of any of the solutions following extended storage when compared to the initial results acquired on the day of preparation.
Conclusion: The data presented has demonstrated the physicochemical stability and bioactivity of a range of KANJINTI™ (trastuzumab) solutions when prepared using controlled and validated aseptic processes, stored protected from light for extended periods at 2°C–8°C and subjected to in-use temperatures. The stability demonstrated in multi-dose bags and elastomeric devices provides additional preparation options to address different global pharmacy practices and requirements.

Submitted: 19 July 2021; Revised: 30 September 2021; Accepted: 1 October 2021; Published online first: 14 October 2021

Introduction/Study Objectives

KANJINTI™ (trastuzumab; Amgen), a biosimilar for Herceptin® (Roche), is a human epidermal growth factor 2 (HER2)-targeted humanized monoclonal antibody for the treatment of HER-2 positive early and metastatic breast cancer and metastatic gastric cancer [1]. Supplied as a powder for concentrate for solution for infusion, trastuzumab is first reconstituted with sterile water for injection (sWFI) prior to dilution in 0.9% w/v NaCl in polyvinylchloride (PVC), polyethylene (PE) or polypropylene (PP) bags [1]. Monoclonal antibodies are complex molecules and are subject to a variety of degradation routes that can be initiated by many factors including formulation, environment, and manipulations [2], many of which are encountered during preparation, transport and storage. The stability data provided in the Summary of Product Characteristics (SmPC) for the majority of antibody therapeutics has, until recently, usually been limited to 24–48 hours following dilution for intravenous infusion (IV), with statements that from a microbiological point of view, the product should be used immediately. Recently, the SmPCs of many of the originator antibody therapeutic products have been updated to provide extended stability once diluted. For example, the trastuzumab originator, Herceptin®, has seen two updates to the shelf life since August 2018 [3]; from stating that solutions of Herceptin® for IV infusion are physically and chemically stable for 24 hours not exceeding 30°C, the SmPC was updated to 7 days (published on emc on 29/08/2018) and subsequently 30 days at 2°C–8°C (21/03/2019), and 24 hours at temperatures not exceeding 30°C. The same recommendations are provided in the current SmPC for KANJINTI™ (trastuzumab) [1]. Despite the extended stability data provided by SmPCs, the immediate use of the infusion solutions from a microbiological point of view is still advised, otherwise, the in-use storage times and conditions prior to use are the responsibility of the user, with the recommendation that this would not normally be longer than 24 hours at 2°C–8°C unless reconstitution and dilution have taken place under controlled and validated aseptic conditions. Extension of the shelf life of products places more emphasis on the quality of the aseptic preparation; since preparation of such therapeutics varies by region and sometimes takes place on the wards or other locations with poorly controlled aseptic conditions. This is especially prevalent in situations without extended shelf life, as doses are prepared and used in close proximity to the patients. An extended shelf life can allow more economical and efficient use of pharmacy aseptic units and drug, allowing advanced batch preparation, dose banding strategies [4] and vial sharing. Preparation under controlled and validated aseptic conditions not only enhances patient safety but also contributes to cost savings by reducing the waste of these expensive drugs, both by utilizing whole vial volumes and avoiding missed doses caused by patient failing to show for appointments or unexpected delays in treatment, by continued storage of the un-administered drug. For the advantages of shelf-life extension to be realized, reliable stability data is of immense value for allowing the safe preparation, storage and use of the drug preparations.

In the United Kingdom (UK), shelf-life extension can be applied to antibody therapeutic preparations providing there is robust stability data to support it; this allows pharmacy aseptic units to assign an extended shelf life to its own preparations under both Section 10 exemption and under the terms of a Specials Licence. The UK National Health Service (NHS) document ‘A Standard Protocol for Deriving and Assessment of Stability Part 2 – Aseptic Preparations (Biopharmaceuticals), 4th Edition, August 2020’ provides guidance for the design and assessment of a robust stability study in support of shelf-life extension [5]. In other countries, drug solutions are prepared by centralized pharmacies or compounding units for transport to clinical sites, which requires longer storage periods than those recommended by the manufacturer; stability data supporting the in-use period of these drugs is therefore vital to provide assurance of their stability during preparation, storage, transportation and administration. Compounding units in Italy are known to prepare pharmacy bulk packs, essentially multi-dose bags containing concentrated drug, which are supplied to hospital pharmacies. Suitable stability data on such stock preparations allows extended storage by the pharmacy for use in making patient-specific doses. Although not an accepted practice in the UK, stability of reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solution stored refrigerated for up to 63 days in multi-dose IV bags was investigated in this study, with additional assessment on the diluted 0.3 mg/mL and 4 mg/mL in 0.9% w/v NaCl infusion solutions that were prepared from multi-dose bags.

The combination of a population increasing in age, new therapies, speciality medications that require expert administration and longer treatment cycles has resulted in an increased demand on healthcare services with additional pressures on clinicians and pharmacy aseptic services. Ambulatory infusion therapy allows medically stable patients to be treated at home or at alternate sites, reducing the need for lengthy hospital stays and often avoiding the need for hospital admission [6]. In addition to assessing the stability of KANJINTI™ (trastuzumab) infusions in polyolef in IV bags, this study investigated the stability of KANJINTI™ (trastuzumab) infusions in a portable elastomeric infusion system that allows continuous IV administration of medications in any setting; medication is delivered to the patient as the elastomeric ‘balloon’ consistently deflates and pushes solution through the IV tubing and into the catheter/port. However, the materials in the elastomeric pump device differ from the PVC, PE or PP bags that the SmPC describes are compatible for preparation of the diluted KANJINTI™ (trastuzumab) infusion, with the elastomeric balloon made from polyisoprene and tubing which may be primed with solution following preparation. Stability of drug following extended storage in these devices is therefore important to ensure the absence of drug-container interactions.

The stability of the trastuzumab originator (Herceptin®) in ready-to-administer presentations [7-10] and, more recently, stability data on several trastuzumab biosimilars [11-14] has been previously reported. To address the stability requirements of different global pharmacy practices, we have conducted a comprehensive study to investigate the effects of extended storage on the trastuzumab biosimilar, KANJINTI™, using several complementary methods to evaluate the stability of a range of concentrations in different containers and storage regimes, as summarized in Table 1. Study 1 evaluated the stability of 21 mg/mL reconstituted solution stored in IV bags (multi-dose bags) for 6 hours at room temperature (17°C–-23°C; RT) followed by 63 days at 2°C–8°C, and following dilution from pre-stored multi-dose bags in 0.9% w/v NaCl to 0.3 mg/mL and 4 mg/mL, stored for 6 hours at RT followed by 4 days at 2°C–8°C plus 24 hours at 25°C/60% relative humidity (RH), in polyolef in IV bags. Study 2 evaluated the stability of KANJINTI™ (trastuzumab) following dilution in 0.9% w/v NaCl to 0.3 mg/mL, 0.8 mg/mL and 4 mg/mL when stored in polyolef in IV bags and INTERMATE® elastomeric infusion pump devices under different storage regimes, as summarized in Table 1; to present a further stability challenge, all diluted products in Study 2 were prepared using KANJINTI™ (trastuzumab) reconstituted solutions that had been stored in pierced vials at 2°C–8°C, protected from light, for 11 days.

Table 1

Methods

Preparation and storage of KANJINTI™ (trastuzumab) solutions
All KANJINTI™ (trastuzumab) solutions were aseptically prepared by the Royal Liverpool and Broadgreen University Hospitals NHS Trust (RLBUHT) Pharmacy Aseptic Production Unit in a Positive Pressure Isolator. KANJINTI™ (trastuzumab) 150 mg powder for concentrate for solution for infusion (Amgen Inc) was reconstituted with sterile water for injection (sWFI), as instructed in the SmPC [1], to a final concentration of 21 mg/mL trastuzumab. For the purpose of sampling, all IV bags had a non-vented dispensing pin installed into the giving port during aseptic preparation. All concentrated and diluted KANJINTI™ (trastuzumab) solutions were stored protected from light in storage areas that are subject to constant temperature monitoring.

Study 1: For preparation of the multi-dose bags of reconstituted solution, a non-vented dispensing pin was installed into the giving port of a 50 mL NaCl 0.9% w/v solution for infusion VIAFLO® bag (Baxter), and the contents withdrawn using a sterile 50 mL syringe, ensuring the removal of as much solution as possible. The contents of seven reconstituted KANJINTI™ (trastuzumab) vials were combined and added to an empty 50 mL VIAFLO® bag. Three bags (A1, A2, A3) were prepared for initial testing (T0) prior to storage at RT (17°C–23°C) for 6 hours followed by 2°C–8°C storage for 63 days. Testing was carried out following 7 days, 20 days, 41 days and 63 days of storage.

A further three multi-dose bags of reconstituted KANJINTI™ (trastuzumab) solution were prepared (B1, B2, B3) and stored at 2°C–8°C; Bag B1 was stored for 22 days, Bag B2 for 42 days and Bag B3 for 63 days. Following the specified storage period, the concentrated bags were each used to prepare three bags of 0.3 mg/mL and three bags of 4 mg/mL in 0.9 % w/v NaCl, by dilution of the appropriate volume of the reconstituted KANJINTI™ (trastuzumab) solution in 50 mL NaCl 0.9% w/v solution for infusion VIAFLO® bag (Baxter). The 0.3 mg/mL and 4 mg/mL solutions were tested on the day of preparation (T0), prior to storage at RT (17°C–23°C) for 6 hours followed by 4 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH, after which final testing was carried out.

Study 2: Following reconstitution of KANJINTI™ (trastuzumab) 150 mg powder for concentrate for solution for infusion vials as instructed by the SmPC [1], the rubber stopper of each vial was pierced an additional three times in different locations using a 19G needle and stored at 2°C–8°C for 11 days. These pierced vials (PV) were diluted to f inal concentrations of 0.3 mg/mL, 0.8 mg/mL and 4 mg/mL in 100 mL NaCl 0.9% w/v solution for infusion VIAFLO® bags (Baxter; 3 bags of each concentration) or INTERMATE® SV System 100 mL/h (Baxter; 3 devices of each concentration). The diluted solutions were tested within 2 hours of preparation (T0), prior to storage at RT (17°C–23°C) for 6 hours followed by 2°C–8°C storage. KANJINTI™ (trastuzumab) 0.3 mg/mL solutions were stored refrigerated for 21 days prior to transfer to 25°C/60%RH storage for 24 hours, with testing after 7 days, 14 days, 21 days and 22 days storage; 0.8 mg/mL and 4 mg/mL solutions were stored refrigerated for 76 days plus an additional 48 hours at 25°C/60%RH, with testing after 14 days, 35 days, 56 days, 76 days, 77 days and 78 days storage. Note that two sets of 0.8 mg/mL and 4 mg/mL VIAFLO® bags were prepared as indicated in Table 1; Set 2 was used for bioassay and assessment of trastuzumab concentration by SEC-HPLC and were stored for total of 79 days, see Table 1, with testing after 14 days, 35 days, 56 days, 77 days, 78 days and 79 days storage. Set 1 was used for all other tests. For clarity of presentation, results from Set 1 and Set 2 bags are listed with the total storage time of 78 days to represent the shortest storage period.

Sampling for analysis
All sampling and testing (with the exception of the bioassay) was performed at Quality Control North West Liverpool, UK, which is hosted by the Liverpool University Hospitals NHS Foundation Trust. Initial testing was performed within 2 hours of sample preparation, prior to storage of samples. At subsequent time points, containers were removed from storage and allowed to equilibrate to room temperature (protected from light) for 30 mins. Prior to sampling, each container was gently inverted 10 times and left to stand for 2 mins to eliminate gas bubbles. Sampling from containers was carried out in a Class II Safety Cabinet using aseptic technique. A pre-cut (4 cm) Lectrocath Line was attached to the Dispensing Pin on each of the IV bags using the Luer Lock connection and an appropriate volume of sample was drained and collected from each bag for testing; separate aliquots were collected for sub-visible particle count analysis. The Lectrocath Line was then disconnected from the bag. For the INTERMATE® pump device products, the initial 2 mL was drained to a separate tube (to remove sample stored in the delivery tube) and visually inspected prior to dispensing to waste. The appropriate volume of sample was then drained and collected from each device for testing; separate aliquots were collected for subvisible particle count analysis. Samples for bioassay testing were collected in Cryovials with External Thread, Self-Sealing Cap (1.0 mL, Skirted; Starlab (UK) Ltd). Cryovials were immersed into liquid nitrogen for 1 min then stored at -80°C. Following sampling, the containers were returned to the appropriate storage area for testing at subsequent time points. Samples for bioassay testing were stored at -80°C until all time points had been collected; they were then transferred to Amgen Inc. under dry ice storage for bioassay analysis at the Attribute Sciences Potency and Characterization Laboratory, USA.

Forced degradation (aged samples)
A series of ‘aged’ trastuzumab samples were prepared for use as system suitability samples to demonstrate the stability-indicating ability of the analytical techniques employed. A vial of KANJINTI™ (trastuzumab) 150 mg powder for concentrate for solution for infusion was reconstituted as per SmPC [1] to produce a 21 mg/mL reconstituted solution, which was stored exposed to ambient temperature (17°C–23°C) and natural daylight; an aliquot of this solution was withdrawn at intervals (specified in Table 2) over 89 days and diluted with 0.9% w/v NaCl to 0.3 mg/mL.

Table 2

Appearance by visual inspection
Solution colour, clarity and particulate formation were monitored by visual inspection of a single sample from each container. Following sampling, each KANJINTI™ (trastuzumab) sample was viewed in the clear colourless sample tube against a white background to assess colour and against a black background for clarity and compared to a sample of distilled water as a reference. Samples were also viewed in their containers for the presence of visible particles using a light magnifier. Particular attention was made to the sample in the delivery line of the INTERMATE® devices for evidence of precipitation.

pH
pH was determined based on Ph. Eur. Method 2.2.3 [15], using a Mettler Toledo SevenMulti™ pH meter and a Mettler Toledo InLab® MicroPro-ISM probe or InLab® ExpertPro probe. The instrument was calibrated using pH 4.00, pH 7.00 and pH 9.00 certified buffer solutions (SPEX CertiPrep) prior to measuring KANJINTI™ (trastuzumab) samples that were equilibrated to a temperature of 20°C–25°C.

Size Exclusion Chromatography (SEC)
The trastuzumab monomer concentration and % ratio of the trastuzumab monomer, high molecular weight species (HMW; e.g. dimers, trimers, higher order aggregates) and low molecular weight species (LMW; e.g. fragmentation products) was determined by size-exclusion chromatography-HPLC (SEC-HPLC) using a validated stability-indicating method on an Agilent 1100 Series HPLC system with UV detector. Chromatographic results were collected by data handling software [Agilent OpenLab CDS (Version A.01.04) EZChrom Edition (Version A.04.04) or OpenLab CDS Version 2.4]. The chromatographic separation was performed at ambient temperature on a Tosoh Bioscience TSK gel G3000 SWXL column (7.8 mm x 30.0 cm) using a mobile phase composition of 25 mM Na2HPO4, 25 mM NaH2PO4, and 0.3 M NaCl, pH 6.8. Mobile phase was filtered through a 0.45 μm Nylon filter membrane under vacuum prior to use. An isocratic flow rate of 0.8 mL/min was maintained for a run time of 26 mins per injection for Standards, 21 mg/mL and 4 mg/mL samples. The run time was extended to 40 mins for 0.3 mg/mL and 0.8 mg/mL product samples due to a peak eluting around 26 mins that was attributable to the VIAFLO® bag contents. A detection wavelength of 220 nm was used with an injection volume of 50 μl. The autosampler tray temperature was maintained at 5°C throughout the analysis.

The 0.3 mg/mL samples were injected without further dilution, 0.8 mg/mL, 4 mg/mL and 21 mg/mL samples were diluted to 0.3 mg/mL with 0.9% w/v NaCl. The trastuzumab monomer concentration in each sample was determined by assaying against three freshly prepared trastuzumab standards, prepared at each time point from KANJINTI™ (trastuzumab) powder for concentrate for solution for infusion (Amgen) to give nominal concentrations of 0.375 mg/mL, 0.3 mg/mL and 0.225 mg/mL trastuzumab; results were calculated as a % of the initial trastuzumab monomer concentration at T0. The method was quantitatively validated in terms of precision, accuracy, linearity, stability of analytical solutions, robustness, limit of detection (LOD), limit of quantification (LOQ) and selectivity. The stability-indicating ability of the method was confirmed through forced degradation studies.

Non-Reducing (NR) and Reducing (RED)-Capillary Gel Electrophoresis (CGE)
To monitor the purity of trastuzumab, CGE was performed under both non-reducing and reducing conditions using a deltaDOT High Performance Capillary Electrophoresis platform, HPCE-512TC (deltaDOT Ltd, UK), using a 32.7 cm 50 μm I.D. fused silica capillary with a 20 cm separation length. Separation of SDS-protein complexes was achieved using SDS-MW Gel Buffer (Beckman Coulter). The capillary and sample carousel were maintained at 22°C. Separation was monitored on-column at 214 nm by diode array. CGE results were collected by P3Controller software and analysed using P3Eva software (deltaDOT Ltd, UK). Both NR- and RED-CGE methods were validated in terms of linearity, precision, stability of solution, LOQ and selectivity. Samples were analysed alongside a reduced protein size standard (MW Sizing Standard; Beckman Coulter) and a trastuzumab standard that was freshly prepared from KANJINTI™ (trastuzumab) powder for concentrate for solution for infusion (Amgen) to be matched in terms of matrix and concentration to the analytical samples. KANJINTI™ (trastuzumab) 0.3 mg/mL and 0.8 mg/mL samples were used without dilution, KANJINTI™ (trastuzumab) 21 mg/mL and 4 mg/mL samples were diluted to 0.3 mg/mL (Study 1) or 0.8 mg/mL (Study 2) with 0.9% w/v NaCl prior to preparing SDS-protein complexes by combination with a concentrated SDS sample buffer (600 mM Tris-HCl pH 9.0 containing 10% SDS). For NR-CGE, each SDS-trastuzumab complex was alkylated with Iodoacetamide (IAM), added to a f inal concentration of 30 mM prior to heating at 70°C for 10 mins. A system suitability sample was prepared without the addition of IAM and heated to 100°C for 10 mins to induce fragmentation. Samples were introduced on to the capillary hydrodynamically at 10 psi for 20 secs and separated at 16 kV (reverse polarity) for 37 mins. For RED-CGE, each SDS-trastuzumab complex was reduced by adding 3% v/v 2-mercaptoethanol prior to heating at 70°C for 10 mins. Samples were introduced on to the capillary hydrodynamically at 10 psi for 10 secs and separated at 16 kV (reverse polarity) for 31 mins. Analysis of a forced degraded (aged) sample demonstrated the stability-indicating nature of the method.

Capillary Zone Electrophoresis (CZE)
Charge variants were analysed by Capillary Zone Electrophoresis (CZE), performed on a deltaDOT HPCE-512TC (deltaDOT Ltd, UK), using a 61.1 cm 50 μm I.D. fused silica capillary with a 48.8 cm separation length. CZE separations were performed in a buffer comprised of 0.05% HPMC, 500 mM EACA, 1.9 mM TETA, pH 5.7. All samples were injected hydrodynamically at 0.5 psi for 10 secs and separated at 20 kV (standard polarity) for 42 mins. The capillary was maintained at 25°C, the sample carousel was held at 16°C. All detection was at 214 nm by diode array. The CZE method was validated in terms of linearity, precision, stability of solution, LOQ and selectivity. KANJINTI™ (trastuzumab) 0.3 mg/mL and 0.8 mg/mL samples were used for CZE analysis without further dilution; KANJINTI™ (trastuzumab) 21 mg/mL and 4 mg/mL samples were diluted to 0.3 mg/mL (Study 1) or 0.8 mg/mL (Study 2) with 0.9% w/v NaCl. Samples were analysed alongside a trastuzumab standard that was freshly prepared from KANJINTI™ (trastuzumab) powder for concentrate for solution for infusion (Amgen) to be matched in terms of matrix and concentration to the analytical samples. Analysis of a forced degraded (aged) KANJINTI™ (trastuzumab) sample, exposed to ambient conditions (ambient temperature and natural daylight), was used to demonstrate the stability-indicating ability of the CZE system.

Sub-visible particle count analysis
Particle counting was performed using a HIAC 9703+ liquid particle counter and accompanying PharmSpec software (Beckman Coulter), with analysis based on the US Pharmacopeia (USP) monograph USP41<787> [16]. Test samples were allowed to equilibrate to ambient temperature prior to testing; 5 x 0.5 mL counts were performed; the first reading was discarded, and the remaining results averaged.

Bioassay
A cell-based proliferation inhibition assay was performed using the human breast tumour cell line, BT-474, which expresses human epidermal growth factor receptor 2 (HER2), the target antigen for trastuzumab. BT-474 cells were incubated with varying concentrations of KANJINTI™ (trastuzumab) reference standard, control and test samples. The endpoint detection reagent CellTiter-Glo® was used to determine the number of viable cells. When incubated with cells, this reagent produces a luminescence signal that is proportional to the amount of adenosine triphosphate (ATP) present, which is directly proportional to the number of viable cells, and inversely proportional to the concentration of the drug. The biological activity of the test sample was determined by comparison of the test sample response to that of the Reference Standard (relative potency). The final reported result is the arithmetic mean of 3 individual determinations.

Results

Visual inspection
Study 1: The reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solutions stored in 50 mL VIAFLO® bags were clear and colourless on the day of preparation (T0), but were observed as clear, very pale-yellow solutions following 7 days storage at 2°C–8°C, which remained throughout 63 days storage. No visible particles were detected at any time point. The appearance of the reconstituted solutions did comply with the description provided in the SmPC [1] for reconstituted KANJINTI™ (trastuzumab), which states it as ‘a colourless to pale-yellow transparent solution’ that ‘should be essentially free of visible particulates’.

KANJINTI™ (trastuzumab) 0.3 mg/mL and 4 mg/mL in 0.9% w/v NaCl samples were clear colourless solutions with no detectable visible particulates, when prepared from 22 day and 42 day stored multi-dose bags and stored refrigerated for 4 days plus 24 hours at 25°C/60%RH. Diluted 0.3 mg/mL and 4 mg/mL samples prepared from 63 day stored multi-dose bag of reconstituted KANJINTI™ (trastuzumab) solution appeared as clear very pale-yellow solutions with a few small translucent particles on the day of preparation; although only a few particles were detected, it was noted that these were more prominent in the 0.3 mg/mL products compared with the 4 mg/mL products. Although the pale-yellow colour remained, the particles were not visible following storage at 2°C–8°C for 4 days plus 24 hours at 25°C/60%RH.

Study 2: All samples remained clear and colourless for the duration of the respective study (0.3 mg/mL: 21 days refrigerated plus 24 hours at 25°C/60%RH; 0.8 mg/mL and 4 mg/mL: 76 days refrigerated plus 48 hours at 25°C/60%RH), with no visible precipitates or particulate matter detected.

pH
Study 1: No significant change was observed for the pH of the reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solutions stored in 50 mL VIAFLO® bags stored refrigerated for 63 days; the mean pH throughout the duration of the study was pH 6.11, which is in agreement with that stated for the reconstituted solution in the SmPC [1], which states a pH of approximately 6.1. All three bags remained within 0.15 pH units of the initial pH at T0 at each time point. The pH of the diluted 4 mg/mL samples prepared from the 22 day, 42 day and 63 day stored multi-dose bags of reconstituted KANJINTI™ (trastuzumab) solution all remained close to pH 6.1, whereas the diluted 0.3 mg/mL bags had a lower average of pH 5.9, most likely reflecting the lower buffering capacity of the excipients. The 4-day refrigerated plus 24 hours at 25°C/60%RH storage had no significant effect on the pH of the diluted samples at either concentration, see Figure 1A.

Study 2: The 0.3 mg/mL samples in IV bags recorded a higher pH than those in Study 1, with a mean pH of 6.17 across the study when stored refrigerated for 21 days plus 24 hours at 25°C/60%RH, however, the 0.3 mg/mL samples had a lower average pH when stored in INTERMATE® pumps (mean pH5.78), see Figure 1B. The 0.8 mg/mL and 4 mg/mL samples in IV bags and the 4 mg/mL sample in INTERMATE® pumps all remained close to pH 6.10 throughout 76 days refrigerated storage plus 48 hours at 25°C/60%RH (mean of pH 6.12, pH 6.15 and pH 6.10, respectively, across all time points), however, the pH of the 0.8 mg/mL sample stored in INTERMATE® pumps was noticeably lower with a mean of pH 5.88 across the time points, see Figure 1C.

The overall observed results of the two studies would indicate that storage of low concentrations of trastuzumab in INTERMATE® pumps in this case 0.3 mg/mL to 0.8 mg/mL, does result in a reduction of the pH of the samples, which may be due to the reduced capacity of the excipients to buffer the pH effects of the INTERMATE® pump device upon interaction with the drug solution. The pH of 0.3 mg/mL, 0.8 mg/mL and 4 mg/mL samples did not vary significantly from their respective initial pH’s at T0, regardless of container, with the average pH (n = 3) of each sample type remaining within 0.24 pH units of T0 at the final time point.

Monitoring of monomer content by SEC-HPLC
SEC-HPLC analysis detected the trastuzumab monomer peak with a retention time (Rt) of approximately 10.1 mins in all sample and standard chromatograms, with minor peaks detected at 8.4 mins, attributed to the dimer, and 15.6 mins, which was identified as the excipient histidine. Any secondary peaks detected were monitored as potential HMW or LMW products throughout the study and calculated as a percentage of total peak area (excluding the histidine peak area). Analysis of the forced degraded (aged) KANJINTI™ (trastuzumab) samples showed signs of progressive degradation with increased exposure times to ambient conditions, indicated primarily by a reduction in monomer and concurrent increase in secondary peak areas for HMW and LMW products, see Figure 2A and Table 2, demonstrating the stability indicating ability of the method. In contrast, the monomer represented on average 99.08% ± 0.16% in all test samples, regardless of concentration, container or study length. A summary of the monomer, HMW and LMW content and trastuzumab concentration in Study 1 and 2 samples are shown in Tables 3 and 4, respectively. Example chromatograms from the final time point of the 78-day study are presented as a worst case with regards to study duration, overlaid with the chromatogram of freshly prepared reference standard for comparison in Figure 2B, indicating no additional peaks or evolution of HMW or LMW products following 6 hours at RT + 76 days at 2°C–8°C + 48 hours at 25°C/60%RH.

Trastuzumab concentration by SEC-HPLC
To monitor the potential adsorption of trastuzumab onto the container walls, the monomer concentration was assessed at each time point and remained within 98.72%–101.90% of the initial concentration for samples, regardless of starting concentration, container or study duration, see Tables 3 and 4.

Monitoring of aggregation by SEC-HPLC
A minimum peak area equivalent to 0.05% of the initial trastuzumab monomer peak area (at T0) in each sample type was applied; any secondary peaks with an area less than this for each standard and sample chromatogram were disregarded.

Study 1: The only HMW peak detected in the reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solutions stored in 50 mL VIAFLO® bags and the diluted 0.3 mg/mL and 4 mg/mL samples prepared from the multi-dose bags was that attributed to the dimer, which remained consistent in the 21 mg/mL multi-dose bags throughout 63 days storage at 2°C–8°C, accounting for ≤1.04% of the total peak area in all three bags and increasing by no more than 0.13% from the initial content. The level of dimer decreased from the initial content at T = Day 0 in all 0.3 mg/mL products following 4 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH (maximum 0.09% decrease detected) and remained consistent in 4 mg/mL products (maximum 0.02% increase detected). The average HMW content of three containers tested in each study is summarised in Table 3.

Table 3

Study 2: The only HMW peak detected in 0.8 mg/mL and 4 mg/mL test samples following 76 days storage at 2°C–8°C plus 48 hours at 25°C/60%RH was that attributable to the dimer, which increased from the initial content at T = Day 0 by ≤0.06% in 0.8 mg/mL samples and by ≤0.13% in all 4 mg/mL samples, regardless of container, following 76 days storage at 2-8°C plus 48 hours at 25°C/60%RH. In addition to the peak considered as the dimer (Rt = 8.4 mins), an additional peak was detected at Rt = 6.4 mins in 0.3 mg/mL sample chromatograms at time points T7 and T14 only, that represented ≤0.11% of the total peak area. The HMW products detected in KANJINTI™ (trastuzumab) 0.3 mg/mL in 0.9% w/v NaCl samples remained consistent throughout 21 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH, accounting for ≤0.93% of the total peak area and remaining within ± 0.16% of initial HMW content, regardless of container. The average HMW content of three containers tested in each study is summarized in Table 4.

Table 4

Monitoring of fragmentation by SEC-HPLC
A minimum peak area equivalent to 0.05% of the initial trastuzumab monomer peak area (at T0) in each sample type was applied; any secondary peaks with an area less than this for each standard and sample chromatogram were disregarded. The histidine peak area was monitored and remained consistent (with a mean range of 3.66%–3.73% during the longest storage period of 78 days for 0.8 mg/mL and 4 mg/mL strengths in both IV bags and INTERMATE® pumps). The area of any LMW peaks (excluding histidine) were combined and expressed as a percentage of the total peak area.

Study 1: No LMW products with peak areas exceeding the applied minimum area were detected in any of the KANJINTI™ (trastuzumab) 21 mg/mL reconstituted solutions stored in 50 mL VIAFLO® bags throughout 63 days storage at 2°C–8°C. LMW products were only detected in 0.3 mg/mL samples diluted from 63 day stored multi-dose bag and remained consistent with no more than 0.08% detected at T0 or following 4 days storage at 2°C–8°C plus 25°C/60%RH in any of the three bags. The average LMW content of three containers tested in each study is summarised in Table 3.

Study 2: The highest level of LMW products was detected in 0.8 mg/mL products stored in INTERMATE® pumps; however, this was never more than 0.30% throughout the duration of the study in any of the three devices. LMW products accounted for less than 0.11% in 0.8 mg/mL KANJINTI™ (trastuzumab) bags and less than 0.07% in 4 mg/mL samples, regardless of container, following 76 days storage at 2°C–8°C plus 48 hours at 25°C/60%RH. No LMW products with peak areas exceeding the applied minimum area were detected in KANJINTI™ (trastuzumab) 0.3 mg/mL in 0.9%w/v NaCl when stored in VIAFLO® bags or INTERMATE® pumps throughout 21 days storage at 2°C–8°C, plus additional 24 hours at 25°C/60%RH. The average LMW content of three containers tested in each study is summarized in Table 4.

Purity by NR-CGE
Fragmentation of trastuzumab in the system suitability sample resulted in the intact antibody (2-Heavy-2-Light chains; 2H2L) being well resolved from impurities, such as the Light chain (L), Heavy chain (H), Heavy-Light chain (HL), Heavy-Heavy chain (HH) and 2-Heavy-1-Light chain (HHL), see Figure 3B. These impurities were used as markers for the detection of fragments in the KANJINTI™ (trastuzumab) test samples. A progressive decrease in intact trastuzumab (2H2L) content and an increase in detected fragments in the test samples would have been indicative of degradation, as demonstrated in the aged KANJINTI™ (trastuzumab) samples, see Figure 3A and Table 2, however no such trend was observed; the NR-CGE profile at each time point was comparable with that at the initial time point, indicating no significant degradation of the drug throughout the duration of the study. The average initial and final content of LMW degradation products and monomer of the three containers tested in each study is summarized in Table 5 with representative electropherograms in Figure 3.

Table 5

Study 1: The 2H2L content in all reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solutions stored in 50 mL VIAFLO® bags remained ≥95.3% in each of the three bags at each time point and was comparable to the level detected in the standard (≥95.7%). The 2H2L content in all 0.3 mg/mL and 4 mg/mL samples diluted from the concentrated stock bags remained ≥95.8% following 4 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH, regardless of the age of the stock bag it was prepared from.

Study 2: There was no detectable loss in purity of trastuzumab in KANJINTI™ 0.8 mg/mL and 4 mg/mL samples stored refrigerated for 76 days plus 48 hours at 25°C/60%RH, with 2H2L content remaining above 96.2% in both VIAFLO® bags and INTERMATE® pumps at the final time point, comparable to the reference standard (96.4%). The 2H2L content in KANJINTI™ (trastuzumab) 0.3 mg/mL products remained ≥93.0% at each time point and was comparable to the level detected in the standard (≥94.7%).

Purity by RED-CGE
CGE was performed under reducing conditions for determination of purity of the heavy (H) and light (L) chains, measured as the sum of H+L. RED-CGE analysis of the aged system suitability sample indicated a reduction in the % Peak Area of the H chain, with additional peaks of higher molecular weight (HMW), one of which was below the level of detection in the Control (freshly prepared) sample, resulting in a decrease in the % Purity (H+L) and H:L ratio, see Table 2 and Figure 4, demonstrating the stability-indicating ability of the reducing CGE system. In contrast, the RED-CGE profile of the test samples at each time point was comparable with the initial profile at the respective T0, indicating no significant degradation of the drug throughout the duration of the study. The average % purity of three containers tested in each study is summarized in Table 5 with example electropherograms in Figure 4.

Study 1: The purity in each KANJINTI™ (trastuzumab) 21 mg/mL reconstituted solution stored in 50 mL VIAFLO® bags was ≥98.0% for the duration of the study and was comparable to that detected in the standard (≥97.7%), remaining within 1.2% of the initial content at T0 following 63 days refrigerated storage. A loss in purity of no more than 1.2% was observed in all three 0.3 mg/mL samples diluted from the concentrated stock bags following 4 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH, regardless of the age of the stock bag it was prepared from; a maximum 2.5% loss in purity was detected in 4 mg/mL bags, which had been prepared from the 63-day stored concentrated stock bag. The H+L purity in 4 mg/mL bags prepared from 22-day and 42-day old-concentrated stock bags remained within 1.8% of the initial content after 4 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH.

Study 2: The purity of H+L chains in each 0.8 mg/mL and 4 mg/mL sample was ≥97.5% at the final time point (T = 76 hours + 48 hours) and was comparable to that detected in the standard, which remained ≥97.4% at each time point; all samples remained within 0.9% of the initial purity in both IV bags and INTERMATE® pumps at the final time point. There was no detectable loss in purity in 0.3 mg/mL samples over 21 days refrigerated storage plus 24 hours at 25°C/60%RH, which remained within 1.6% of the initial purity at each point.

Charge variant analysis by CZE
CZE was used to evaluate the distribution of charged variants, with peaks grouped as basic, main or acidic variants. Analysis of the aged sample, exposed to ambient temperature and daylight for 27 days to induce degradation, demonstrated an 11.1% reduction in main peak with a concurrent 12.3% increase in acidic charge variants, see Table 2 and Figure 5. These results agree with those of Vieillard et al. 2018 for another trastuzumab biosimilar, which showed a significant increase in acidic variants following 28 days storage at 22°C, detected by weak cation exchange chromatography [11]. For the KANJINTI™ (trastuzumab) samples under test, the charge profile of each demonstrated no significant change in the % content of main, basic or acidic charge variants, and remained consistent throughout the duration of each study with the profile obtained at the initial time point, regardless of the storage container. The average % basic, main and acidic variants of three containers tested in each study is summarized in Table 6 with example electropherograms in Figure 5.

Table 6

Study 1: The average main peak content for the three bags (77.87%) following 63-day refrigerated storage of the reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solutions stored in 50 mL VIAFLO® bags was comparable to the average initial content at T0 (77.24%), with no significant changes to the acidic or basic variants, see Table 6. The main peak in each 0.3 mg/mL and 4 mg/mL sample diluted from the concentrated stock bags did not decrease by more than 2.1% following 4 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH, regardless of the age of the stock bag it was prepared from.

Study 2: There was no detectable loss in trastuzumab main peak in KANJINTI™ 0.8 mg/mL and 4 mg/mL samples in VIAFLO® or INTERMATE® pumps with an average maximum 1.51% decrease in % main peak observed following 76 days refrigerated storage plus 48 hours at 25°C/60%RH; the main peak content remained ≥76.8% at each time point regardless of container, comparable to that in freshly prepared standard (≥77.8% at each time point). Similarly, there was no significant loss in main peak in 0.3 mg/mL stored in VIAFLO® or INTERMATE® pumps following 21 days refrigeration plus 24 hours at 25°C/60%RH, with an average maximum 0.79% reduction.

Sub-visible particle count analysis
The quantification of sub-visible particles is important for ensuring the quality and safety of therapeutic protein preparations, since the presence of mobile undissolved particles can pose a danger to patients receiving the drug. With the exception of the reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solutions stored in 50 mL VIAFLO® bags, particles >10 μm and >25 μm were quantified in all 0.3 mg/mL, 0.8 mg/mL and 4 mg/mL KANJINTI™ (trastuzumab) samples at the initial, mid (where applicable) and final time point of each study and are summarized in Figure 6. All products complied with the limits stated in USP<787> for sub-visible particulate matter in therapeutic protein injections and in British Pharmacopoeia (BP) 2019 Appendix XIII A: Particulate contamination: Sub-visible particles (Ph. Eur. method 2.9.19) for solutions for infusion or solutions for injection supplied in containers with a nominal content of 100 mL or less (≤6,000 per container equal to or greater than 10 μm and ≤600 per container equal to or greater than 25 μm) [16, 17].

Bioactivity by inhibition of cell proliferation bioassay
The bioassay was performed on initial (T0) and final time point samples taken for each set of KANJINTI™ (trastuzumab) test samples. The determined % Relative Potency results were calculated relative to the % bioactivity obtained at the initial time point (T0), which was designated as 100%, to identify any significant change in biological activity following the extended storage periods. There were no significant changes in the % bioactivity in any of the KANJINTI™ (trastuzumab) test samples across all concentrations and containers following the various storage durations. The mean potency of three containers in each set of samples is presented in Table 7.

Table 7

Study 1: The biological potency of the concentrated stock bags of reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solutions stored refrigerated for 63 days was consistent with the initial potency across all three bags (100%–102%). Diluted 0.3 mg/mL and 4 mg/mL samples, prepared from 63-day refrigerated concentrated stock bag of reconstituted KANJINTI™ (trastuzumab) 21 mg/mL solution, were assessed as they represented the greatest stability challenge with regards to storage duration and each sample maintained 89%-97% of the initial potency following 4 days storage at 2°C–8°C plus 24 hours at 25°C/60%RH.

Study 2: There was a consistent biological potency in KANJINTI™ (trastuzumab) 0.8 mg/mL and 4 mg/mL samples in VIAFLO® or INTERMATE® pumps stored for 76 days at 2°C–8°C plus 48 hours at 25°C/60%RH, with all samples retaining 93%–107% of their respective initial potency, and 0.3 mg/mL samples retaining 97%–110% potency following 21 days refrigeration plus 24 hours at 25°C/60%RH.

Discussion

This study has used a range of analytical techniques to evaluate the stability of KANJINTI™, a trastuzumab biosimilar, to address the requirements of different global pharmacy practices: Study 1 was designed to assess the stability of reconstituted solution (21 mg/mL) when stored refrigerated in 50 mL multi-dose bags, and following subsequent dilution in 0.9% w/v NaCl for shorter term storage in polyolef in bags at f inal concentrations of 0.3 mg/mL and 4 mg/mL; Study 2 assessed the stability of KANJINTI™ (trastuzumab) 0.3 mg/mL, 0.8 mg/mL and 4 mg/mL in 0.9% w/v NaCl solutions when stored in polyolef in IV bags and ambulatory devices. All studies included a 6-hour storage period at RT (17°C–23°C) following initial sampling for T0 analysis and prior to refrigeration to cover the timeframe and conditions that products may be subjected to during preparation/handling, prior to use. Diluted KANJINTI™ (trastuzumab) products were subjected to 24 hours to 48 hours storage at 25°C/60%RH at the end of the refrigeration storage period to allow assessment of stability at the in-use temperature they will be administered and provide data for evaluating the effect of temperature excursions. Products were prepared aseptically in a hospital aseptic manufacturing unit so that the acquired stability data represented the manufacturing processes that would typically be used.

Forced-degraded samples are often used to demonstrate the stability-indicating ability of analytical techniques employed, however, the conditions used to degrade the sample, e.g. dramatic change in pH, temperature or oxygen level, may have an unrepresentative effect on the molecular structure of proteins [5]. This study utilized KANJINTI™ (trastuzumab) 21 mg/mL reconstituted solutions, exposed to ambient conditions (17°C–23°C and natural daylight) for extended periods of time prior to dilution with 0.9% w/v NaCl, to challenge the stability-indicating nature of the analytical methods. These ‘aged’ products were representative of the ‘natural’ degradation routes followed by the trastuzumab molecule when stored for extended periods outside of the recommended storage conditions (2°C–8°C and protected from light), demonstrating the progressive degradation that occurs in unfavourable storage conditions. Changes were detected after just 27 days exposure, notably increased aggregation and fragmentation with concurrent reduction in monomer as detected by SEC, increased fragmentation detected by NR-CGE, a decrease in % purity of heavy and light chains detected by RED-CGE, and altered distribution of charge variants detected by CZE, resulting in increased acidic variants, likely due to deamidation which is considered as a common degradation pathway for proteins [4]. An increase in acidic variants at 22°C has been detected in another trastuzumab biosimilar (Herzuma®) [11]. Previous studies on stability of the trastuzumab originator (Herceptin®) have indicated ready-to-administer infusion solutions (0.4 mg/mL–4 mg/mL) stored in polypropylene bags are stable for 28 days when stored at room temperature without light protection [7] and in polyolef in bags at 0.8 mg/mL–2.4 mg/mL for 6 months at 20°C ± 2°C, protected from light [9], with no evidence of physicochemical instability. The changes to the trastuzumab molecule stored at ‘ambient’ temperatures and exposed to natural daylight in the present study have occurred in the concentrated 21 mg/mL reconstituted solution, in the presence of undiluted excipients and demonstrate that room temperature and the effects of light exposure should not be underestimated.

The production of multi-dose bags of concentrated drug, supplied as pharmacy bulk packs to hospitals for dilution in making patient-specific doses, is not a widely used practice; however, this study has provided evidence that the reconstituted solution retains its physicochemical properties and biological activity following 63 days storage at 2°C–8°C and following dilution to 0.3 mg/mL and 4 mg/mL in 0.9% w/v NaCl IV bags, stored refrigerated for 4 days plus 24 hours at 25°C/60%RH.

The use of solutions from previously pierced vials is not a recommended practice in the NHS in the UK. We had previously determined the stability of reconstituted KANJINTI™ (trastuzumab) (21 mg/mL) stored in the vial following 11 days storage at 2°C–8°C, protected from light (unpublished data) and the stability of 0.3 mg/mL–4 mg/mL KANJINTI™ (trastuzumab) product in 0.9% w/v NaCl was further challenged by using 11-day-old reconstituted solutions stored in pierced vial for their preparation. Whereas the stability of 0.8 mg/mL–4 mg/mL products was assessed over a total of 78 days, the stability assessment of 0.3 mg/mL solutions was limited to a total of 22 days since it has been stated that 0.3 mg/mL KANJINTI™ (trastuzumab) solutions are rarely used clinically [14] and there is a tendency for lower concentrations of biological molecules to be less stable, likely related to dilution of stabilizing excipients [5]. The stability of KANJINTI™ (trastuzumab) 0.3 mg/mL–3.8 mg/mL in 0.9% w/v NaCl IV bags for 35 days at 2°C–8°C has previously been reported [14], the current study has provided additional stability data for this concentration range by including storage in INTERMATE® pumps, allowing the option of ambulatory infusion therapy.

The most obvious differences between the drug presentations were in the pH of the lower dose samples stored in INTERMATE® pumps; the pH of 0.3 mg/mL and 0.8 mg/mL solutions stored in INTERMATE® pumps were lower compared with storage in IV bags (maximum difference of 0.45 units and 0.26 units, respectively), whereas 4 mg/mL solutions returned a similar pH regardless of container (max. difference of 0.07 units). The lower pH is likely due to the reduced capacity of the excipients in lower doses (due to dilution) to buffer the pH effects of the INTERMATE® pump upon interaction with the drug solution, this seemingly had no effect on stability since the pH of lower dose samples did not vary significantly from their respective initial pH at T0, regardless of container, and no sign of instability was detected by the other analytical methods. There was no significant change (defined as 0.5 pH unit; [5]) in the pH of any of the tested solutions over the respective storage periods.

There was no change in trastuzumab monomer concentration in any of the samples regardless of dilution, container or study length indicating no adsorption of the drug to the containers. This is particularly pertinent for the KANJINTI™ (trastuzumab) solutions stored in the INTERMATE® pumps, since the protein is in contact with different materials to those stated to be compatible in the SmPC [1], including the elastomeric balloon (polyisoprene) and tubing, providing supporting data for the absence of drug-container interaction when storing monoclonal antibodies in these ambulatory devices. The combined data from SEC and CGE indicated that there was no evidence of aggregate formation or fragmentation in any of the solutions during the storage periods, whilst CZE detected no significant changes in the charge variant distribution, suggesting that there had been no chemical modification leading to degradation. Sub-visible particles in all solutions and containers complied with the Ph. Eur. method 2.9.19 limits [17] whilst the bioassay data demonstrated that the extended storage periods did not affect the biological potency of the KANJINTI™ (trastuzumab) preparations.

A limitation to the present study is that transport simulation was not performed, however the effect of mechanical stress to simulate transportation has been reported for KANJINTI™ (trastuzumab) infusion products in IV bags prepared at similar concentrations to this study (0.3 mg/mL–3.8 mg/mL) [14] with no adverse effect on stability. The nature of the INTERMATE® pumps would result in less agitation of the solution within the elastomeric balloon, suggesting mechanical stress may have less effect on solutions stored in these devices. Microbiological stability, aseptic processes, transport processes and associated risks should be independently assured by the user. The lack of data to detect particles in the 0.1 μm–1μm range is also considered a limitation of the study, since submicronic particles can reflect early signs of protein destabilization and the beginning of aggregation. Sub-visible protein particles in the 0.1 μm–10 μm, as well as those >10 μm, have the potential to impact the safety and efficacy of a product over its shelf life [18]. Despite the characterization gap for submicron particles in the 0.1 μm–1 μm range, SEC analysis, which can characterize soluble aggregates in the range of 10 nm–100 nm [19], did not indicate any evolution of dimer or aggregate formation. The sub-visible particle counts in the 2 μm–5 μm range were also monitored by light obscuration, which detected varying numbers throughout the different storage durations (supplementary data). There was no obvious or consistent trend although the most variability was associated with the lower 0.3 mg/mL concentrations; variability was also observed in the control containers containing 0.9% w/v NaCl diluent only.

The present study has provided additional stability data on the trastuzumab biosimilar KANJINTI™ when prepared in both concentrated multi-dose bags and following dilution and extended storage in IV bags and elastomeric devices. Extended shelf lives based on stability data should be as short as practicable [5], however, the extended stability data provides storage options that allow the infusions to be prepared in advance under controlled and validated aseptic conditions, contributing to increased patient safety and a reduction in drug waste. The stability demonstrated in the portable elastomeric device may provide the option to treat patients outside of the hospital environment, reducing the need for hospital admission.

Conclusion

The combined data from a range of stability-indicating analytical methods has demonstrated the in-use physicochemical stability and bioactivity of the trastuzumab biosimilar KANJINTI™ when prepared in controlled validated aseptic conditions and stored for extended periods, in both concentrated multi-dose bags (21 mg/mL) and following dilution in IV bags and elastomeric devices (0.3 mg/mL–4 mg/mL), to address the stability requirements of different global pharmacy practices.

For patients

Drugs often have to be diluted to prepare the correct dose to give to a patient and it is important to ensure that the diluted drug does not deteriorate during storage. This study has tested the quality of the drug KANJINTI™ (trastuzumab) before and after it has been diluted and stored for different lengths of time in different containers. The results indicated that KANJINTI™ (trastuzumab) remains stable at both high and low doses that are commonly used after storage in a fridge and during a period of time at room temperature. This means that the drug infusion can be prepared in advance and stored refrigerated until required, reducing cost and saving clinician time. As well as being stable in infusion bags, the study has indicated that the drug is stable in a portable elastomeric device that may allow patients to be treated outside of the hospital environment; this may provide clinicians and patients with increased treatment options.

Acknowledgements

The authors would like to thank the Royal Liverpool and Broadgreen University Hospitals NHS Trust (RLBUHT) Pharmacy Aseptic Production Unit for preparation of samples and Kristen Elson (Amgen, Thousand Oaks, CA, USA) for providing guidance and direction throughout the study.

Funding sources

This study was funded by Amgen Inc.

Competing interests: Jolene Teraoka, Jill Crouse-Zeineddini and Jane Hippenmeyer are Amgen employees and stockholders. Sarah Elizabeth Lee is an employee of Baxter Healthcare. Quality Control North West Liverpool is a hosted service of Liverpool University Hospitals NHS Foundation Trust. The testing performed by Quality Control North West Liverpool was funded by Amgen Inc.

Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Lyndsay Davies¹, PhD
Katie Milligan¹, BSc
Mark Corris¹, BSc
Ian Clarke¹, Medical Technical Officer
Paul Dwyer¹, MSc
Sarah Elizabeth Lee², PhD
Jolene Teraoka³, BSc
Jill Crouse-Zeineddini³, PhD
Jane Hippenmeyer⁴, PharmD

¹Quality Control North West – Liverpool, Pharmacy Practice Unit, 70 Pembroke Place, Liverpool L69 3GF, UK
²Baxter Healthcare Corporation, 25212 IL-120, Round Lake, IL 60073, USA
³Amgen Inc. Attribute Sciences, Thousand Oaks, CA 91320, USA
⁴Amgen (Europe) GmbH, 22 Suurstoffi, CH-6343 Rotkreuz, Switzerland

References
1. Electronic Medicines Compendium (emc). Kanjinti 150 mg powder for concentrate for solution for infusion (Summary of Product Characteristics). Last updated on emc: 25-01-2021 [homepage on the Internet]. [cited 2021 Sep 30]. Available from: https://www.medicines.org.uk/emc/product/9233/smpc
2. Le Basle Y, Chennell P, Tokhadze N, Astier A, Sautou V. Physicochemical stability of monoclonal antibodies: a review. J Pharm Sci. 2020;109(1):169-90.
3. Electronic Medicines Compendium (emc). Herceptin 150 mg powder for concentrate for solution for infusion. History of updates. Last updated on emc: 24-08-2020 [homepage on the Internet]. [cited 2021 Sep 30]. Available from: https://www.medicines.org.uk/emc/product/3856/smpc/history
4. Bardin C, Astier A, Vulto A, Sewell G, Vigneron J, Trittler R, et al. Guidelines for the practical stability studies of anticancer drugs: a European consensus conference. Ann Pharm Fr. 2011;69(4):221-31.
5. Santillo M, Davies L, Austin P, Campbell C, Castano M, Marks C, et al. A standard protocol for deriving and assessment of stability, Part 2 – Aseptic preparations (biopharmaceuticals) incorporating annex on antibody drug conjugates. 4th Edition, August 2020.
6. Kenny K. Ambulatory infusion therapy. Pharmacy Times. 2015;81(9).
7. Kaiser J, Kramer I. Physiochemical stability of diluted trastuzumab infusion solutions in polypropylene infusion bags. Int J Pharm Compd. 2011;15(6):515-20.
8. Pabari RM, Ryan B, Ahmad W, Ramtoola Z. Physical and structural stability of the monoclonal antibody, trastuzumab (Herceptin®), intravenous solutions. Curr Pharm Biotechnol. 2013;14(2):220-5.
9. Paul M, Vieillard V, Da Silva Lemos R, Escalup L, Astier A. Long-term physico-chemical stability of diluted trastuzumab. Int J Pharm. 2013;448(1):101-4.
10. Nalenz H, Köpf E, Dietel E. Prolonged in-use stability of reconstituted herceptin in commercial intravenous bags. Int J Pharm Compd. 2018;22(5):417-23.
11. Vieillard V, Astier A, Paul M. Extended stability of a biosimilar of trastuzumab (CT-P6) after reconstitution in vials, dilution in polyolefin bags and storage at various temperatures. Generics and Biosimilars Initiative Journal (GaBI Journal). 2018;7(3):101-10. doi:10.5639/gabij.2018.0703.022
12. Kim SJ, Lee JW, Kang HY, Kim SY, Shin YK, Kim KW, et al. In-use physicochemical and biological stability of the trastuzumab biosimilar CT-P6 upon preparation for intravenous infusion. BioDrugs. 2018;32(6):619-25.
13. Yun J, Kim J, Chung J, Hwang S-J, Park SJ. Extended stability of reconstituted and diluted SB3 (trastuzumab biosimilar) assessed by physicochemical and biological properties. Adv Ther. 2019;36(7):1700-14.
14. Crampton S, Polozova A, Asbury D, Lueras A, Breslin P, Hippenmeyer J, et al. Stability of the trastuzumab biosimilar ABP 980 compared to reference product after intravenous bag preparation, transport and storage at various temperatures, concentrations and stress conditions. Generics and Biosimilars Initiative Journal. 2020;9(1):5-13. doi:10.5639/gabij.2020.0901.002
15. British Pharmacopoeia Commission. Determination of pH values (Ph. Eur. Method 2.2.3) British Pharmacopoeia 2020. Volume V. Appendix L.
16. United States Pharmacopeia. Sub visible particulate matter in therapeutic protein injections, light obscuration particle count test. United States Pharmacopeia and National formulary 2018. 41<787>.
17. British Pharmacopoeia Commission. Particulate contamination: sub visible particles, method 1, light obscuration particle count test. (Ph. Eur. Method 2.9.19) British Pharmacopoeia 2020. Volume V. Appendix XIIIA.
18. Carpenter JF, Randolph TW, Jiskoot W, Crommelin DJ, Middaugh CR, Winter G, et al. Overlooking subvisible particles in therapeutic protein products: gaps that may compromise product quality. J Pharm Sci. 2009;98(4):1201-5.
19. Wong NA, Uchida NV, Dissanayake TU, Patel M, Iqbal M, Woehl TJ. Detection and sizing of submicron particles in biologics with interferometric scattering microscopy. J Pharm Sci. 2020;109(1):881-90.

Author for correspondence: Lyndsay Davies, PhD, Senior Pharmaceutical Biochemistry Analyst, Quality Control North West – Liverpool, Pharmacy Practice Unit, 70 Pembroke Place, Liverpool L69 3GF, UK

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 10/05/2024

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Pharmacokinetics and bioequivalence of generic etoricoxib in healthy volunteers

Posted on August 30, 2021

Author byline as per print journal: Nishalini Harikrishnan¹, BSc; Ka-Liong Tan², DPhil; Kar Ming Yee³, BPharm; Alia Shaari Ahmad Shukri¹, MSc; Nalla Ramana Reddy⁴, MBBS; Chuei Wuei Leong³, PhD

Introduction/Study Objectives: A bioequivalence study was performed to compare the pharmacological profile of innovator etoricoxib (ETO) with a newly developed generic ETO, both in a 120 mg tablet formulation. A dissolution study was conducted to optimize the formulation process before evaluating physical changes in the active pharmaceutical ingredient and the formulated product.
Methods: This was a randomized, open-label, balanced, two-treatment, two-period, two-sequence, single-dose, two-way crossover, truncated bioequivalence study involving a washout period of ten days. A total of 26 healthy male volunteers were recruited. The pharmacokinetic profile of the test formulation was compared with the reference formulation.
Results/Discussion: The pharmacokinetic parameters of ETO were calculated based on the plasma drug concentration-time profile using non-compartmental analysis to determine its safety profile and tolerability. The Test/Reference (T/R) ratio of ETO was 104.36% (90% confidence interval (CI): 98.30%–110.80%) for area under curve (AUC)_0-72 while the T/R ratio of maximum concentration (Cmax) was 101.39% (92.15%–111.56%). The 90% CI of the Cmax and AUC_0-72 of ETO were within acceptable bioequivalence limits of 80%–125%. All values were within the predetermined limits of the Association of Southeast Asian Nation (ASEAN) bioequivalence guidelines.
Conclusion: The test formulation was found to be bioequivalent with respect to the reference drug, according to ASEAN bioequivalence guidelines.

Submitted: 19 May 2021; Revised: 26 August 2021; Accepted: 26 August 2021; Published online first: 8 September 2021

Introduction/Study Objectives

Etoricoxib (ETO), which has the chemical formula 5-chloro-6’-methyl-3-[4-(methylsulfonyl) phenyl]-2, 3’-bipyridine, see Figure 1, is a highly selective non-steroidal cyclooxygenase (COX)-2 inhibitor with a molecular weight of 358.84 g/mol. Cyclooxygenase catalyses the production of prostaglandins and exists in two isoforms, namely COX-1 and COX-2. Inhibition of COX-2 reduces the production of prostaglandins, leading to anti-inflammatory and analgesic effects. COX-2 also plays a role in ovulation, implantation and closure of the ductus arteriosus in newborns, and regulates certain functions of the renal and central nervous systems such as the induction of fever, perception of pain and cognition [1].

ETO has been shown to produce dose-dependent inhibition of COX-2 at doses up to 150 mg/day. However, it does not inhibit the synthesis of gastric prostaglandin or exert any effects on platelet function [2]. Thus, it can be ingested orally to relieve the acute pain associated with rheumatoid arthritis, psoriatic arthritis, osteoarthritis, gout, back pain, headache, or inflammation secondary to dental surgery [3].

In terms of pharmacokinetics, ETO shows good oral absorption with an absolute bioavailability of approximately 100%. Peak plasma concentration, maximum concentration (C_max), of 3.6 μg/mL was reached one hour after the administration of 120 mg ETO in fasting adults [4] with an area under curve (AUC) of 37.8 μg.hr/mL. Furthermore, the pharmacokinetics of ETO are linearly related to the clinical dose range [4]. Onset of action of ETO can occur from 24 minutes after administration. Approximately 92% of administered ETO is bound to human plasma protein with a concentration range of 0.05 μg/mL–5 μg/mL. At steady state, the volume of distribution (Vd_ss) is approximately 120 L in humans.

ETO undergoes extensive metabolism; fewer than 1% is excreted as the parent compound in urine. ETO metabolism is catalysed by cytochrome P450 (CYP) enzymes before forming 6’-hydroxymethyl derivatives. Further oxidation of the 6’-hydroxymethyl derivative leads to the formation of the principal metabolites from ETO metabolism, i.e. the 6’-carboxylic acid derivatives of ETO. These principal metabolites act as weak COX-2 inhibitors with minimal or no measurable activity. None of the principal metabolites are COX-1 inhibitors.

A generic drug should have the same dosage, strength, route of administration, safety profile, quality, and performance characteristics as the innovator product [5]. Generic versions of ETO are often preferable in view of their equivalence to the innovator and their availability at a lower cost. A bioequivalence (BE) study in compliance with the Association of Southeast Asian Nation (ASEAN) Guidelines is required to establish therapeutic equivalence between the generic and innovator formulations before any new generic products can be registered under the National Pharmaceutical Regulatory Agency in Malaysia. Therefore, this study aimed to determine the BE of a generic ETO (120 mg, tablet formulation) in comparison to the innovator product, Arcoxia® (120 mg, tablet formulation).

Methods

Subjects and study design
This was a randomized, open-label, balanced, two-treatment, two-period, two-sequence, single-dose, two-way crossover, truncated trial with a washout period of 10 days. The study recruited 26 healthy male volunteers aged between 18–45 years with a body weight of ≥ 45 kg and body mass index (BMI) ranging from 18.5 to 30.0 kgm^-2. The mean age, height, weight, and BMI of the participants were 32.69 ± 6.30 years, 169.5 ± 6.74 cm, 71.07 ± 10.05 kg, and 24.7 ± 2.6 kg/m², respectively. Researchers monitored contraindications, hypersensitivities and other potential risks of treatment among participants. Vital signs (blood pressure, pulse rate) were measured at pre-dose, 1.00, 3.00, 9.00, 25.00, 33.00 and 50.00 hours after dosing. Table 1 shows the demographic characteristics of the subjects, who were selected based on predetermined eligibility criteria. Subjects medical history was obtained and physical examination was performed to record blood pressure, radial pulse rate, body temperature and respiratory rate. Electrocardiogram and other clinical laboratory evaluations were carried out, including evaluations of HIV 1 and 2 antibody status, hepatitis B surface antigen, hepatitis C virus antibodies, tests for venereal disease, and tests for common drugs of abuse (amphetamine, barbiturates, benzodiazepines, morphine, tetrahydrocannabinols and cocaine) 21 days prior to the study commencing.

This BE study number No. 152-18 (as referenced by the independent ethics committee) followed the International Conference on Harmonisation Good Clinical Practice and the ASEAN guidelines on the conduct of BE studies [6]. All subjects were informed about the objectives, procedures, and potential risks of participation in the study and all subjects signed an informed consent form before enrolling in the study. The trial protocol received approval from the Maarg Independent Ethics Committee, an independent ethics committee regulated by the Indian Drug and Cosmetic Act and the 2008 Declaration of Helsinki. Analysis was performed by RA Chem Pharma Limited, Hyderabad, India (Clinical Research and Biosciences Division).

Table 1

Test products
The test product, etoricoxib tablet 120 mg (Batch No.1908296PB) was manufactured by Duopharma Manufacturing Bangi Sdn Bhd, Malaysia. The reference product, Arcoxia® ETO tablet 120 mg (Lot No. 83882064) was manufactured by Frosst Iberica, SA, Spain.

Dissolution test
A dissolution study was conducted to compare the test and reference products prior to the BE study. It was performed using the Electrolab dissolution test system, in accordance with United States Pharmacopeia (USP) general methods. A high-performance liquid chromatography system (Agilent, 1260 Infinity, India) equipped with model software was used to quantify the samples. The Metrohm model AG/913 (India) was used to determine the pH of all solutions with 0.45 μm nylon membranes procured from Millipore, India.

Treatment phase and blood sampling
Subjects underwent at least ten hours of fasting before sampling. A total of 23 sampling points were planned. A pre-dose sample was collected as the baseline. Subjects received either a single dose of test product or reference product along with 240 mL of water. Blood samples were collected at 0.25, 0.50, 0.75, 1.00, 1.25, 1.50, 1.75, 2.00, 2.25, 2.50, 2.75, 3.00, 3.50, 4.00, 6.00, 8.00, 10.00, 12.00, 24.00, 36.00, 48.00 and 72.00 hours post-administration. The samples were centrifuged at 4,000 rpm for 10 minutes at 4°C. Plasma samples were transferred to the bioanalytical department in dry ice and stored at -80°C until analysis.

Analysis of drug concentration
Liquid chromatography tandem mass spectrometry (LC-MS/MS) was conducted to analyse the samples. The analyte ETO and its internal standard etoricoxib D₄ were separated with the analytical column Phenomenex, C₁₈, 50 x 4.6 mm, 5 μm. This method produced a linear response in the plasma ETO concentration in the K² EDTA blood tube over a concentration range of 10.28–5,479.52 ng/mL. The method has been validated for its selectivity, intra-batch and inter-batch precision, accuracy, recovery, stability, linearity, and sensitivity. Liquid-liquid extraction was completed using Phenomenex, C18, 50 x 4.6 mm, 5 μm column to extract ETO from the plasma.

Statistical analysis
Statistical analysis was performed using SAS® software version 9.4 (SAS Institute Inc, Cary, NC, USA) using the non-compartmental method in Phoenix® WinNonlin (Version 8.0) to identify the pharmacokinetic values of C_max and AUC of the drug. ANOVA analysis was performed on the Ln-transformed pharmacokinetic parameters using the General Linear Model (PROC GLM). The BE of the test formulation was established within a 90% CI such that the relative means of C_max and AUC_0-72were expected to fall within 80%–125% of that of the reference formulation.

Results/Discussion

Comparative dissolution was conducted at pH 1.2, 4.5, and 6.8. At pH 1.2, more than 85% of the active ingredient dissolved within 15 minutes. At pH 4.5 and pH 6.8, the similarity factors were 43.8 and 50.8, respectively. The accepted similarity factor range is above 50 [6]. At pH 4.5, the dissolution of the test formulation behaves differently due to its variation in excipient compositions compared to the reference. Tables 2 and 3 compare the dissolution profile of the test formulation against the reference formulation, whereas Figures 2, 3 and 4 show the dissolution profile of test formulation plotted against reference formulation.

Table 2

Table 3

To determine the test and reference product’s comparative bioavailability, a BE study must be performed. We therefore recruited 26 healthy male subjects of South Asian heritage who fulfilled the inclusion criteria. All subjects received both the test and reference products and were included in the pharmacokinetic and safety analysis. No serious adverse events (SAEs) were reported. However, two adverse events (AEs) were reported: fever and headache not associated with nausea and vomiting during first phase (of the crossover) after the administration of reference product, and fever not associated with any other symptoms during the first phase after the administration of test product. Both AEs were categorised as mild. No clinical biochemistry values or vital signs met the predefined criteria of Potential Clinical Importance.

Table 4 shows the pharmacokinetic parameters for the test and reference products. In this study, the pharmacokinetic parameters of the ETO tablet were assessed based on the plasma concentrations of ETO. The T/R ratios of ETO were 104.36% (90% CI interval: 98.30%–110.80%) for AUC_0-72 and 101.39% (92.15%–111.56%) for C_max. The T_max for the test and reference products were 1.063 and 1.156 hours, respectively. Furthermore, intra-subject variability was low for both C_max and AUC_0-72 as the CV (%) did not exceed 30% for any parameter. The AUC_0-72 and C_max of the test formulation passed the acceptance criteria for BE as the 90% CI of the AUC_0-72 and C_max of the test and reference formulations fell within the range of 80%–125% according to guidelines. The AUC_0-72 and C_max of ETO were also within an 80%–125% range.

Table 4

Figure 5 shows the mean plasma concentration versus time after oral administration of 120 mg ETO tablet (both the test and reference products). The highest intra-subject coefficient of variation was found to be 15.3% for C_max.

A similar study was previously conducted in Saudi Arabia [4]. In this study, the AUC_0-72 for the test product was 23,067.30 ± 8,978.36 as compared to 23,478.20 ± 9,719.32 for the reference product. The C_max was 1,923.90 ± 466.83 for the test product and 1,986.14 ± 614.41 for the reference product. As the BE was within a range of 80%–125%, the test product was deemed to be bioequivalent to the innovator [4]. In comparison, our study reported that the 90% CI observed for C_max was 92.15%–111.56%, higher than the 89.76%–106.81% reported in the Saudi Arabian study. Similarly, the AUC_0-72 of 98.30%–110.80% in the current study is also slightly higher than the 95.72%–102.48% reported in the previous study [4]. The difference could be due to the ETO formulations and study populations.

A further study administered a 60 mg formulation of ETO among healthy volunteers in Mexico [7]. The geometric mean ratios of C_max and truncated AUC_0-72 were 99.55%–119.33% and 95.97%–103.06%, respectively. Thus, the test product was also deemed bioequivalent to the reference product in this study. Furthermore, a single dose study of ETO 60 mg was conducted in 24 healthy subjects in Bangladesh [8]. In this study, the AUC_0-120 reported was 85.37%–107.74% with a C_max of 85.54%–111.98%, indicating that the test and reference formulation of ETO met the regulatory criteria for BE. Finally, a similar study comparing the reference product (Arcoxia) against a test product produced by PT Dexa Medica in 26 healthy subjects was conducted in Indonesia. The results also showed bioequivalence, with a AUC_0-72 of 98.70%–108.32% and a C_max of 100.18%–119.18%.

The current study had a sufficient number of subjects to ensure adequate statistical power to prove the equivalency of the test product to the reference product. However, the study has some limitations. Due to recruitment capacity, we could only include male volunteers. This is because the use of ETO is not recommended in women who are trying to conceive due to evidence of an increased risk of miscarriage, and no women who are unable to conceive, e.g. post hysterectomy, volunteered to participate in the study [10].

Conclusion

This study intended to assess the bioavailability of a newly developed etoricoxib (120 mg, tablet formulation) in comparison to the innovator preparation, Arcoxia® (120 mg, tablet formulation). Based on the study results, we conclude that the new etoricoxib 120 mg tablet meets bioequivalence guidelines.

Funding sources

This work was financially supported by a Duopharma R & D fund (Purchase Order No. 4100225052). Pharmacological evaluation support was provided by KL Tan, DPhil during an industrial internship, funded by Duopharma Biotech Berhad.

Disclosure

The study TCTR identification number is TCTR20210714009 (https://www.thaiclinicaltrials.org/show/TCTR 20210714009).

This study received ethical approval from the independent ethics committee with permits from India Central Drugs Standard Control Organisation. Informed consent was obtained from all subjects.

Prior presentations: None.

Competing interests: This work was financially supported by the Duopharma R & D fund. KL Tan received a subsidy from Duopharma Biotech Berhad, Malaysia during an industrial internship at Universiti Sains Islam Malaysia (USIM) for a bioequivalence study of ETO.

Provenance and peer review: Not commissioned; externally peer reviewed.

Authors

Nishalini Harikrishnan¹, BSc
Ka-Liong Tan², DPhil
Kar Ming Yee³, BPharm
Alia Shaari Ahmad Shukri¹, MSc
Nalla Ramana Reddy⁴, MBBS
Chuei Wuei Leong³, PhD

¹Outsource R&D, Duopharma Innovation Sdn Bhd, No. 2 Jalan Saudagar U1/16, Zon Perindustrian Hicom Glenmarie, Seksyen U1, 40150 Shah Alam, Selangor, Malaysia
²Pharmacology Unit, Faculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Persiaran Ilmu, Putra Nilai, 71800 Nilai, Negeri Sembilan, Malaysia
³Formulation and R&D Technologies, Duopharma Innovation Sdn Bhd, No. 2 Jalan Saudagar U1/16, Zon Perindustrian Hicom Glenmarie, Seksyen U1, 40150 Shah Alam, Selangor, Malaysia
⁴RA Chem Pharma Limited, Clinical Research and Biosciences Division, Plot No. 26 & 27, Technocrat Industrial Estate (TIE), Balanagar, Hyderabad 500037, India

References
1. Martina SD, Vesta KS, Ripley TL. Etoricoxib: a highly selective COX-2 inhibitor. Ann Pharmacother. 2005;39(5):854-62.
2. Dallob A, Hawkey CJ, Greenberg H, Wight N, De Schepper P, Waldman S, et al. Characterization of etoricoxib, a novel, selective COX-2 inhibitor. J Clin Pharmacol. 2003;43(6):573-85.
3. Brooks P, Kubler P. Etoricoxib for arthritis and pain management. Ther Clin Risk Manag. 2006;2(1):45-57.
4. Omaima N, Rana H, Bassam A, Idkaidek N, Naji M. Bioequivalence evaluation of two brands of etoricoxib 120 mg tablets (etoricoxib-SAJA & ARCOXIA®) – in healthy human volunteers. Mod Clin Med Res. 2017;1:7-12.
5. Dunne S, Shannon B, Dunne C, Cullen W. A review of the differences and similarities between generic drugs and their originator counterparts, including economic benefits associated with usage of generic medicines, using Ireland as a case study. BMC Pharmacol Toxicol. 2013;14:1.
6. National Pharmaceutical Regulatory Agency. ASEAN Guidelines: The conduct of bioavailability and bioequivalence studies. 2015 [homepage on the Internet]. [cited 2021 Aug 26]. Available from: https://www.npra.gov.my/images/reg-info/BE/BE_Guideline_FinalMarch2015_endorsed_22PPWG.pdf
7. Araceli G, Medina-Nolasco KLO-C, Lopez-Bojorquez E, Arellano-Ibañez MA, Burke-Fraga V, Gonzalez-de la Parra M. Bioequivalence of two oral formulations of etoricoxib 60 mg tablets in healthy Mexican adults. Am J Bioavailab Bioequiv. 2018;1(1):010-4.
8. Shohag MH, Islam MS, Ahmed MU, Joti JJ, Islam MS, Hasanuzzaman M, et al. Pharmacokinetic and bioequivalence study of etoricoxib tablet in healthy Bangladeshi volunteers. Arzneimittelforschung. 2011;61(1):617-21.
9. Tjandrawinata RR, Setiawati A, Nofiarny D, Susanto LW, Setiawati E. Pharmacokinetic equivalence study of nonsteroidal anti-inflammatory drug etoricoxib. Clin Pharmacol. 2018;10:43-51.
10. MEDSAFE. New Zealand Consumer Medicine Information. 2020 [homepage on the Internet]. [cited 2021 Aug 26]. Available from: https://www.medsafe.govt.nz/Medicines/infoSearch.asp

Author for correspondence: Chuei Wuei Leong, PhD, Formulation and R&D Technologies, Duopharma Innovation Sdn Bhd, No. 2 Jalan Saudagar U1/16 Zon Perindustrian Hicom Glenmarie Seksyen, U1 Shah Alam, 40150 Shah Alam, Selangor, Malaysia

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 10/05/2024

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Reasons for patients’ generic drug switching at the pharmacy counter: a pilot study

Posted on February 23, 2021

Author byline as per print journal: Pieter J Glerum^1,2, MSc; Mert Hayta^1,3, PharmD, MSc; David M Burger⁴, PharmD, PhD; Cees Neef⁵, PharmD, PhD; Marcel L Bouvy³, PharmD, PhD; Marc Maliepaard^1,6, PhD

Background: Drug switching describes switching between drug products with the same active substance. Drug switching occurs commonly in the Netherlands and mostly between generic drug products, however, the specific reasons for switching are incompletely understood.
Objective: To document reasons for drug switches between products with the same active substance in the Netherlands.
Methods: Observational field research was conducted in a total of 16 pharmacies in the Netherlands during November and December 2019. A single researcher recorded the reasons for drug switches at each pharmacy at the time of their occurrence, for one working day.
Results: In total, 207 drug switches were recorded. Most drug switches were caused by nationwide drug shortages (32%, n = 66) and the Dutch price-based tender system (23%, n = 47). Other reasons for switching included deals between pharmacists and wholesalers (12%, n = 25), distribution issues at wholesalers (11%, n = 22), and a financially favourable margin for pharmacists (11%, n = 21).
Conclusion: This study indicates that drug shortages and the Dutch price-based tender system are likely to be major causes of drug switches in the Netherlands. However, other reasons, such as drug product distribution issues and local economic incentives, were also identified.

Submitted: 17 December 2020; Revised: 9 February 2021; Accepted: 11 February 2021; Published online first: 24 February 2021

Background/Objective

Drug switches between products with the same active substance occur commonly in the Netherlands and mostly between two generic drug products [1]. Drug switching should not be clinically problematic, as interchangeability is supported by the demonstration of bioequivalence [2]. However, a number of patients, physicians and pharmacists have a negative perception of generic drugs and drug switching [3], and indeed some adverse reactions related to drug switches have been reported [4]. This clinical discomfort should be avoided.

Nonetheless, generic drugs are cheaper than their branded counterparts and are therefore important to reduce the costs of pharmaceutical care. In search of an optimum balance between the clinical discomfort, some patients experience and financial benefits, patients would benefit from a system in which generic drugs have a large market share, but the number of drug switches is small. A first step towards this is to elucidate how drug switches arise.

The reasons for the occurrence of drug switches are not yet fully understood. Logically, drug shortages will result in drug switches, but other reasons can be found in the actions of health insurers, prescribers, wholesalers and/or patients, which can influence the choice of the dispensed drug product. Reasons may differ between countries as a result of legislation and healthcare system differences. However, in many countries, similar policies and financial incentives are in place to promote the use of generic drugs. For instance, a number of countries have tender systems in place which favour the cheaper drug product for reimbursement from a group of interchangeable drug products [5].

This study was performed in the Netherlands, where generic drugs have a large market share and there is a price-based tender system to promote generic drug use [6], as well as mandatory prescribing by International Nonproprietary Name (INN). The number of drug shortages has increased in the Netherlands in the last decade [7] as a result of several issues related to production, distribution and quality. The Netherlands is also a less favourable sales market compared to other countries, due to low prices and a small population size. In this study, we prospectively gathered data at the pharmacy counter, both qualitatively and quantitatively, regarding the underlying reasons for drug switching in the Netherlands.

Methods

Observational field research was conducted in pharmacies in the Netherlands during November and December 2019. A total of 400 pharmacies were approached from the database of the Utrecht Pharmacy Practice network for Education and Research (UPPER) [8]. Pharmacies were selected on the basis of geographical spread and with a maximum 2-hour travel time from the city of Utrecht. The research protocol was approved by the UPPER Institutional Review Board.

Drug switches were recorded on a paper form by one researcher (MH) at each pharmacy’s counter, for one working day. A drug switch was defined as the replacement of a patient’s drug product with a drug product containing the same active pharmaceutical ingredient, at the same strength, in the same dosage form and with the same route of administration, but from a different manufacturer (branded or generic). Drug switches for drugs destined for home delivery or storage in the pharmacy’s service lockers were included in the study, whereas pre-packed and pre-sorted packets for polypharmacy patients were excluded from the study for reasons of practicality. The researcher used software embedded automatic notification systems at each pharmacy where possible, but was also dependent on pharmacy personnel to report drug switches manually.

Pharmacy characteristics (predominant healthcare insurer, ownership status) were recorded. Per drug switch, the reason, INN, dose, manufacturer, and the patient’s health insurance company were recorded. Pharmacists were interviewed regarding their view on drug switching and the reasons behind drug switching. Simple descriptive statistics were performed with Microsoft Excel and R.

Nationwide shortages were identified from Farmanco – the drug shortage report system from the Dutch Pharmacists Association – which lists manufacturer confirmed shortages lasting longer than 14 days [9]. If a drug switch was due to a drug shortage that was neither a result of local pharmacy practice nor described in Farmanco then the reason for the switch was considered to be the result of a distribution issue at the wholesale level.

Results

Out of 400 approached pharmacies, 19 were willing to participate (4.8%). Of these, for 16 pharmacies visits could be scheduled and were included in the study. These pharmacies differed by the predominant health insurance companies: Zilveren Kruis/Achmea (6), Menzis (4), Zorg en Zekerheid (3), VGZ/CZ (2) and Salland (1), and by ownership: pharmacy chain (4), franchise (5), independent (7).

In total, 207 drug switches were recorded; 13 on average per day, per pharmacy (range: 4–24). As expected, most drug switches were between generic products (86%, 177/207). 6% (12/207) of switches were from a brand-name product to a generic product. Drug switches between two brand-name products, e.g. imported from another European country, accounted for 4% (8/207) of switches and switching from a generic product to a brand-name product accounted for 3% (7/207) of switches. Finally, only 1% (3/207) of the drug switches were between compounded products, see Table 1.

As depicted in Figure 1, most drug switches were a result of nationwide shortages (32%, 66/207) or the Dutch tender system (23%, 47/207). Agreements between wholesalers and pharmacists to dispense a drug product from a specific manufacturer were responsible for 12% (25/207) of the recorded drug switches. In addition, 11% (22/207) of the drug switches were presumably caused by wholesalers’ distribution issues, resulting in shortage at the pharmacy, while favourable financial margins were the reason for 10% (21/207) of the drug switches. Moreover, local stock issues at the pharmacy, not caused by wholesalers’ distribution issues, were indicated as the reason for 5% (10/207) of the drug switches. Finally, 4% (8/207) were at the request of the patient, while 3% (7/207) were initiated by the pharmacist, and only one switch (0.5%) was initiated by the prescriber.

During the interview, 12 of the 16 pharmacists (75%) indicated that the number of recorded drug switches was an underestimation of a normal days’ practice, whereas 4 pharmacists (25%) indicated that it was representative. Fifteen pharmacists (94%) reported an annual increase in the number of drug switches. Furthermore, based on daily experience, 11 of the 16 pharmacists (69%) estimated that drug shortages were the main cause for drug switches, while 5 (31%) reported that the Dutch tender system was the main cause. In addition, the majority of pharmacists (9/16, 56%) were of the opinion that generic drugs are interchangeable, while 4 pharmacists (25%) believed that they are not interchangeable. Three pharmacists (19%) had a neutral position on interchangeability.

Discussion

To our knowledge, this study is the first to investigate reasons for the occurrence of drug switches in the Netherlands. In our sample, we found that the two main reasons for drug switching are nationwide drug shortages and the price-based tender system, which, combined, were responsible for approximately 55% of the drug switches we observed.

It could be argued that distribution issues at wholesalers and stock issues at the pharmacy should also be classified as shortages, which would make shortages responsible for 47% (98/207) of the total number of drug switches we observed.

Economic drivers also contribute to drug switches and were identified as reasons for switching in 22% of cases in this study, including deals between pharmacist and wholesalers (12%) and financially favourable margins related to reimbursement (10%).

This study has some limitations, including the small sample size, which could impact the generalizability of the results. In addition, pharmacy visits were only conducted in the months of November and December, while the influence of the Dutch tender system on drug switching is likely bigger in January to March [1]. Future studies could include a larger number of pharmacies and include visits spread throughout the year. However, because we aimed to study the entire range of reasons for drug switching, the research period was still deemed adequate and perhaps more sensitive to issues other than the Dutch tender system.

Second, the study is limited by its semi-systematic approach, as the researcher was partly dependent on pharmacy personnel to report drug switches. Three pharmacies did not use an automatic notification system for drug switches, which increased this dependency. Furthermore, we excluded drug switches for polypharmacy patients in pre-packed and pre-sorted packets. It must also be noted that we only succeeded in scheduling visits on ‘not too busy’ days. These limitations may have resulted in an underestimation of the total number of drug switches. Indeed, during the interview, 75% of pharmacists (12/16) indicated that the recorded number of drug switches was likely an underestimation. However, it is not expected that different reasons for drug switches would have been identified, and so we believe our conclusions on the reasons for drug switches to be robust.

This study presents an exploration of the complex reasons for drug switching in the Netherlands, which are, in some cases, related to policies or market structure specific to the Netherlands. Nonetheless, these findings are of international relevance. The search for an optimized drug market system, in which generic drugs simultaneously have a large market share but a low number of drug switches, is not restricted to the Netherlands. Moreover, policies and financial incentives, such as mandatory INN prescribing and price-driven tender systems for drug reimbursement, are implemented in many countries. They would therefore likely result in a similar number of drug switches and similar reasons for those switches. Policymakers worldwide could thus utilize the results of our study. The results should also open up a discussion about the acceptability of economic or distribution issues underlying drug switches, which may result in clinical discomfort for patients. This is, however, a difficult discussion, as the issues are unlikely to be easily solved and influence the financial viability of the pharmaceutical market.

Funding sources

No external funding was received for this research project.

Disclaimer

The opinions in this manuscript are only those of the authors. This manuscript is not intended to reflect the opinion of the Medicines Evaluation Board in the Netherlands nor any of the working parties or scientific committees of the European Medicines Agency.

Ethics

The protocol for this research was approved by the UPPER Institutional Review Board of the division of Pharmacoepidemiology and Clinical Pharmacology of Utrecht University, the Netherlands. For each participating pharmacy, a written informed consent was provided by the head pharmacist.

Authors’ comments

What is already known about this subject:
– Switching between (generic) drugs of the same active substance results in adverse drug reactions
– Drug switching occurs frequently in Dutch pharmacies [1]

What this study adds:
– Knowledge of the reasons for drug switches to occur in the Netherlands
– Evidence to support discussion on policy interventions aiming for a reduction in the number of drug switches

Competing interests: The authors declared no competing interests for this work.

Provenance and peer review:Not commissioned; externally peer reviewed.

Authors

Pieter J Glerum^1,2, MSc
Mert Hayta^1,3, PharmD, MSc
David M Burger⁴, PharmD, PhD
Cees Neef⁵, PharmD, PhD
Marcel L Bouvy³, PharmD, PhD
Marc Maliepaard^1,6, PhD

¹Medicines Evaluation Board, Utrecht, The Netherlands
²Department of Clinical Pharmacy and Toxicology, Maastricht University Medical Centre, Maastricht, The Netherlands
³Department of Pharmacoepidemiology and Pharmacotherapy, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands
⁴Department of Pharmacy, Radboud University Medical Centre, Nijmegen, The Netherlands
⁵Department of Clinical Pharmacy and Toxicology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, The Netherlands
⁶Department of Pharmacology and Toxicology, Radboud University Medical Centre, Nijmegen, The Netherlands

References
1. Glerum PJ, Maliepaard M, de Valk V, Burger DM, Neef K. Drug switching in the Netherlands: a cohort study of 20 active substances. BMC Health Serv Res. 2020;20(1):650.
2. European Medicines Agency. Committee for Medicinal Products for Human use (CHMP). Guideline on the investigation of bioequivalence. 20 January 2010. CPMP/EWP/QWP/1401/98 Rev. 1/ Corr **.
3. Colgan S, Faasse K, Martin LR, Stephens MH, Grey A, Petrie KJ. Perceptions of generic medication in the general population, doctors and pharmacists: a systematic review. BMJ Open. 2015;5(12):e008915.
4. Glerum PJ, Maliepaard M, de Valk V, Scholl JHG, van Hunsel F, vanPuijenbroek EP, et al. Quantifi cation of adverse drug reactions related to drug switches in the Netherlands. Clin Transl Sci. 2020;13(3):599-607.
5. SCRIBD. Tendering system en. Available from: https://www.scribd.com/document/443979055/tendering-systems-en
6. Overheid.nl. Wetten. Regeling – Besluit zorgverzekering [homepage on the Internet]. [cited 2021 Feb 9]. Available from: https://wetten.overheid.nl/BWBR0018492/2021-01-01
7. KNMP. Farmanco. Geneesmiddelentekorten [homepage on the Internet]. [cited 2021 Feb 9]. Available from: https://www.knmp.nl/patientenzorg/geneesmiddelen/geneesmiddelentekorten
8. Koster ES, Blom L, Philbert D, Rump W, Bouvy ML. The Utrecht Pharmacy Practice network for Education and Research: a network of community and hospital pharmacies in the Netherlands. Int J Clin Pharm. 2014;36(4):669-74.
9. KNMP. Farmanco. Dè website voor alle geneesmiddelentekorten. [homepage on the Internet]. [cited 2021 Feb 9]. Available from: https://farmanco.knmp.nl

Author for correspondence: Pieter J Glerum, MSc, CBG-MEB, PO Box 8275, NL-3503 RB Utrecht, The Netherlands

Disclosure of Conflict of Interest Statement is available upon request.

Last update: 10/05/2024

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