Author byline as per print journal: Luther Gwaza1,2, BPharm, MPhil; John Gordon3, PhD; Henrike Potthast4, PhD; Marc Maliepaard5, PhD; Jan Welink5, Hubert Leufkens1,5, PhD; Matthias Stahl6, MD; Alfredo García-Arieta7, PhD
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Abstract: |
Submitted: 21 March 2016; Revised: 11 April 2016; Accepted: 11 April 2016; Published online first: 25 April 2016
Direct comparison within well-designed and well-conducted randomized controlled trials (RCT) is the gold standard for comparing health interventions. The usual practice to obtain marketing authorization for new health interventions is to compare them to placebo, or standard of care, but not with all available health interventions. Some interventions are developed simultaneously, thus it is not feasible to perform comparison between them during this development phase to support marketing authorizations. Moreover, in some cases, there is a relatively large number of available interventions making direct comparison through RCTs between them impractical. Therefore, in these instances where multiple interventions exist, there is often lack of, or insufficient, evidence of direct comparison (head-to-head comparison) to evaluate relative effectiveness of all the available health interventions; indirect comparisons are then employed [1–3].
Indirect treatment comparison is defined as an evaluation of different health interventions using information from independent studies. This is useful when there are no data on direct comparison, or to provide supplementary evidence when the data from direct comparison are insufficient [4]. Indirect comparison can be categorized into naïve (unadjusted), informal indirect comparison, and adjusted indirect comparison [3]. Naïve indirect comparison evaluates the data from the independent studies as if the data are from the same study ignoring the between-study variance. For this reason, evidence from naïve indirect comparison is equivalent to observational studies, prone to bias and it may over- or underestimate the treatment effect; thus this approach is not recommended for analysing data from RCTs [2–4]. In informal indirect comparison, the results from the independent studies are compared directly, and relative effects or statistical significance are not formally calculated [3]. Adjusted indirect treatment comparison evaluates different treatments tested in independent studies modified based on the results of their direct comparison with a common control, partly preserving the power of RCTs [3] without the added cost of actual direct RCT comparison. However, adjusted indirect comparisons are less precise as reflected in wider confidence intervals [4], thus wherever possible direct comparisons should be performed.
Figure 1 illustrates the direct and indirect comparison of health interventions. Suppose there are four different treatments, A, B, C and D compared in three different trials. If treatment A was compared in an RCT with treatment B, treatment C in another RCT with treatment B, and treatment C with D in another RCT, adjusted indirect treatment comparison can be used to compare treatment A and C since both were tested in two independent trials with the common treatment B. Likewise, treatment B and D can be compared using adjusted indirect comparison since both were compared in direct comparison with common treatment C.
Generic medicines are approved nationally following the expiry of patents or market exclusivity period for the innovator products based on demonstration of bioequivalence with the innovator product. A bioequivalence study comparing a generic and an innovator drug is a form of direct comparison. With time, the number of approved generic medicines per active substance generally increases. Thus, requirement for direct comparison through bioequivalence studies between generics is impracticable since several generics of the same drug are licensed at various times, often without knowledge of the other generics under development. For this reason, adjusted indirect treatment comparison is a useful approach to identify those generic drug products whose interchangeability can be assured, by comparing the different generic drug products that have been demonstrated to be bioequivalent with the same reference product, to support or ensure switchability in clinical practice without concerns on efficacy or safety due to the switching.
Several methods are available for performing indirect comparisons: (1) naïve or unadjusted indirect comparisons; (2) statistical methods using aggregate data such as simple weighted combination of separate estimates as suggested by Bucher et al. [1] (adjusted indirect comparison); (3) modelling approaches based on the individual patient data (meta-regression); and (4) mixed treatment comparisons based on Bayesian statistics (logistic regression) [2, 5].
In meta-regression analysis, the estimated difference between the groups (treatment effect) is modelled as a function of one or more study characteristics as the predictor variable. Estimated treatment effect in each study is weighted according to the inverse of its variance. A simple approach for meta-regression is weighted linear regression, and the residual heterogeneity is estimated using random effects. Meta-analysis can be performed using the fixed-effects to describe the residual heterogeneity. The key assumption for fixed effect meta-analysis is that the different trials estimated the same effect, for example, the effect of treatment A relative that of treatment B. Regression methods such as logistic regression can be used to perform indirect comparison using the generalized linear models and individual patient data. With regression modelling, one can adjust for other variables available for each study. While full individual patient data, which are required for logistic regression for indirect comparison, or the estimated treatment effect, its variance and covariates for each trial, which are necessary to perform meta-regression, are rarely publicly available, adjusted indirect comparison is performed using the summarized data available in published articles and approved product labelling. It is the simplest and most appropriate methodological approach when only two interventions are to be compared indirectly as it is the case for bioequivalence studies [6].
When using summarized data extracted from published data, first the data are extracted or calculated using appropriate summary statistics, e.g. confidence intervals, mean ratios, for each set of studies. For bioequivalence studies, the extracted data are study products, sample sizes preferably in each sequence, confidence intervals and study design (fasting or fed study, parallel or crossover, single or multiple dose studies). The confidence intervals of the bioequivalence studies are converted to log scale and used to estimate the point estimate and standard error of the treatment effects. Lastly, the data are combined to provide an overall comparison. The standard statistical result, i.e. the variance of the difference between the two independent estimates, is sum of the two variances (variance is square of the standard error), which is similar to a 2-sample t-test. Thus, using the illustration in Figure 1, if you have the two estimated effects for A υs B and B υs C as θAB and θBC, respectively, the effect of the comparison A υs C is estimated as θAC = θAB − θBC and var (θAC) = var (θAB) + var (θBC) [1]. The scale of the effect θ relates to the scale on which the data would be analysed, such as risk difference, log risk ratio, log odds ratio for binary data, the means, mean difference, mean change for continuous data and log hazard ratio for time-to-event data. In bioequivalence studies, the pharmacokinetic outcome measure is continuous data, and the effect θ is the ratio of log-transformed geometric means of the treatments, e.g. A and B (point estimate). The 90% confidence interval (CI) of the ratio of the log-transformed geometric means is the standard statistical result. Therefore, the 90% CI for the indirect comparison 
, where z/t in this equation is the z value of standardized normal distribution or the t value of the Student’s t distribution that corresponds to the desired level of confidence (90% in case of bioequivalence studies) and the degrees of freedom in the case of the Student’s t distribution.
We explored the different approaches for calculating adjusted indirect comparisons [7]. In this study, we compared six methods that can be used to calculate the width of the confidence intervals based on z distribution (z0.9) or Student’s t distribution (t0.9, d.f.). Four methods that assumed small sample sizes with Student’s t distribution are: (a) Chow and Liu meta-analysis method [8], which assumes all studies had 2 × 2 crossover design and homogeneity of the distribution of reference product data in all studies; (b) homoscedastic method which assumes homogenous variances; (c) heteroscedastic method which assumes heterogeneous variances; and (d) the pragmatic approach which does not require the assumption of homogeneity of variances between studies with small sample sizes. The two methods which assumes large sample sizes with a standardized normal distribution (z0.9) are: (a) Chow and Shao meta-analysis method [9]; and (b) the z-distribution method with no assumption on homogeneity of variances [10].
We concluded that although the differences were minor, the homoscedastic method is recommended, unless there are clear differences in variances, because it is the most conservative approach for estimating the confidence intervals for adjusted indirect comparisons.
We investigated the differences in bioavailability between generics prequalified by the World Health Organization (WHO) using adjusted indirect comparisons [7, 11]. These studies investigated a diverse group of products from the antimalarials artemether/lumefantrine [7], first-line antituberculosis drugs, [11] and first-line antiretroviral drugs with a total of 394 indirect comparisons. In contrast to the ±20% acceptance range used for direct comparisons, a ±30% acceptance range is proposed for adjusted indirect comparisons [7, 11], due to the limited precision of indirect comparisons [1, 4].
First, these studies demonstrated the utility of adjusted indirect treatment comparison to compare the bioavailabilities between generic drug products that had been compared with the same reference product in direct comparisons. Second, the outcome of these comparisons indicate that antimalarial artemether/lumefantrine, first-line anti-tuberculosis, and first-line antiretroviral generics prequalified by WHO can be interchanged without any safety and efficacy concerns in clinical settings. Although some comparisons were outside the conventional acceptance limits of ±20% for direct comparisons, there were no generic–generic comparisons outside the ±30% for indirect comparisons, except one comparison for efavirenz Cmax. Failure to show equivalence within a ±30% acceptance range in one out of 394 adjusted indirect comparisons should be interpreted as insignificant number since it is less than 0.3% of the comparisons.
The results obtained with the prequalified generics are consistent with the outcomes reported elsewhere using data from other regulatory authorities [12–14]. Herranz et al. showed that exposures obtained with generic tacrolimus formulations in the Spanish market were within the ±20% acceptance range based on adjusted indirect treatment comparisons [12]. In addition, results from adjusted indirect comparisons were consistent with those from direct comparisons for multiple generic formulations of gabapentin products marketed in The Netherlands [13]. Using data from bioequivalence studies submitted to the Dutch Medicines Evaluation Board (CBG-MEB) for atorvastatin, bicalutamide, naratriptan, olanzapine, perindopril, venlafaxine, cyclosporine, tacrolimus and mycophenolate mofetil, Yu and colleagues showed that in 80% of the cases the indirect comparisons between generics fulfilled the conventional acceptance limit of ±20%, while the remainder were within ±30% [14]. A point estimate constraint in the bioequivalence studies may be relevant for drugs with a narrow therapeutic index, e.g. cyclosporine and tacrolimus, where switching between generics of these drugs is not restricted. Generally, narrow therapeutic drugs are usually assessed with a narrowed acceptance range, e.g. 90.00–111.11%, to ensure interchangeability with the reference [15–17].
We observed that assurance regarding interchangeability of two generic drug products is reduced when either the point estimate ratios in the original studies are shifted from unity by more than 5% or when the width of the 90% confidence interval is large in the direct comparisons [11]. Therefore, we investigated the influence of point estimate, variability of the pharmacokinetic parameters (Cmax and AUC), and the sample size in the original studies on the ability to demonstrate bioequivalence between generics in the adjusted indirect comparisons [18]. However, sample size and variability are not independent since the sample size is calculated based on the expected variability and the desired statistical power. Thus, statistical power is the most relevant parameter for consideration in the computations.
We calculated the outcome of adjusted indirect comparisons for 14,592 scenarios using 57 possible differences between point estimates from 0% to 14% and 16 possible study powers from 50% to 99.99%. The study results illustrated that demonstrating bioequivalence within the conventional acceptance limits of 80–125% by means of adjusted indirect comparisons is only possible if the difference between the point estimate is small (< 5%) for any sufficiently powered study (> 80%). Furthermore, even when both studies are overpowered, the difference cannot be larger than 14%. This study showed that in cases where generic–generic switching maybe of concern, regulators might consider a point estimate constraint in the original studies.
The variance for the adjusted indirect comparison is additive, 
, thus, the major limitation of adjusted indirect comparisons of bioequivalence studies is the reduced precision. On one hand, the inability to show bioequivalence by means of indirect comparisons is not proof of inequivalence, but it may be simply that there is not enough statistical power to make this conclusion. On the other hand, when bioequivalence is shown within the conventional acceptance limits for indirect comparisons despite the reduced statistical power, we can consider not only that the generic drug products are bioequivalent but also very similar.
The validity of indirect comparisons is dependent on the methodological quality and assumptions. Similarity of trials involved in adjusted indirect comparisons should be carefully assessed to ensure that there are no important differences between the trials under comparison in aspects that could bias the estimated formulation effect. Although standard requirements are applied on the design, conduct and analysis of results of the bioequivalence studies submitted for the prequalification of generics [15], in some cases different study designs might be employed. For example, metabolite versus parent as the analyte, or plasma versus urine as the biological fluid collected for analysis, or multiple versus single dose studies. Studies with these different study designs cannot be compared because the formulation effect cannot be expected to be the same between them. However, we consider results from conventional 2 × 2 crossover designs and replicate designs as combinable. There is no consensus on whether parallel and crossover trials should be combined in indirect comparisons [2], however, this may be possible if the participants and interventions are comparable. In all the analyses performed, all the studies were crossover trials.
In contrast to adjusted indirect comparisons of efficacy trials, confidence in the methodological quality and similarity of adjusted indirect comparisons of bioequivalence studies is assured because of the general consistency in the basic design of these studies. For instance, the characteristics of participants in bioequivalence studies are commonly defined, i.e. usually healthy adult male and/or female volunteers within 18–55 years of age, which controls for the differences in baseline characteristics between treatment groups, whereas differences in disease state in efficacy trials is of concern. The objective of bioequivalence studies is to evaluate formulation differences and external validity of the results is based on the assumption that the effect of the drug in the target populations, i.e. patients would be the same for the test and reference. Nevertheless, in some cases, subject–by–formulation interaction could occur, e.g. when one formulation has excipients that are not tolerated by specific subgroups of patients that are not present in the reference formulation. This is often mitigated by the regulatory requirement to declare such excipients on the product label. Non-randomization of the trials can confound the results if other differences between the treatment groups are linked to the outcomes. Randomization ensures that like is compared with like, i.e. that there are no differences between the groups in any factors other than the intervention itself, in this case, formulation effects. In the bioequivalence studies considered in the analysis of the prequalified generics, subjects were randomized in the allocation of sequence.
Despite the utility of the indirect comparisons, the evidence from such analyses should be interpreted with caution. The internal validity of direct comparisons should be carefully evaluated to reduce bias. In the analysis of the prequalified generics, methodological quality of the studies was not assessed as part of the adjusted indirect comparisons since only the generics that were prequalified were included in the analysis. The prequalification process entails stringent assessment including inspection of the contract research organizations at which the studies were performed, thus providing assurance of the quality of the prequalified product. Therapeutic doses are usually standardized as highest available strength, although in some cases the studies used lower doses. Nonetheless, the results are reported as mean ratios, thus the effect of dose on the outcomes is negligible. The studies were all single dose studies with the same outcome measure of pharmacokinetic parameters Cmax and AUC in all the studies, estimated using validated software. The parent compound in plasma was analysed using validated bioanalytical methods. Despite the general consistency with the bioequivalence studies used in the adjusted indirect comparisons, changes in the requirements over time encompassing several revisions of the guidelines could potentially impact on the methodological quality between studies conducted at different time points; this may be corrected by the use of the same reference product in the different bioequivalence studies. Only the studies using a common reference product as listed by the WHO Prequalification of Medicines Programme were compared in the adjusted indirect comparisons. Though US and European reference products are both accepted in the WHO Prequalification of Medicines Programme, and no distinction was made in the analysis, in some cases these are not the same due to different manufacturing sites and different excipients. However, it is assumed that these products are bioequivalent to the pivotal clinical batch used for gaining marketing authorizations in both jurisdictions.
In conclusion, adjusted indirect comparison is a useful tool to compare relative bioavailabilities between generics that have been compared with a common reference in direct comparison to ensure interchangeability between the generics. The investigated antimalarial – artemether/lumefantrine, first-line antituberculosis and antiretroviral generic drug products prequalified by WHO were considered interchangeable without safety and efficacy concerns. We have also demonstrated that the ability to show bioequivalence between generic drug products by means of indirect comparisons depends on the difference between the point estimates of the bioequivalence studies, which is the point estimate of the indirect comparison, and the power of the bioequivalence studies that are combined. In this respect, concluding equivalence in the indirect comparison within the conventional acceptance limits of 80–125% is only possible when: (a) point estimate difference between generics are low (< 5%) for any sufficiently powered study (> 80%); or (b) the differences do not exceed 14% when both studies are overpowered. Therefore, in cases where it is important to ensure generics interchangeability, the regulatory authorities may consider a point estimate constraint in the original bioequivalence studies. In the general case, due to the reduced precision of indirect comparison, a slightly wider acceptance limits (± 30%) is proposed for indirect comparisons.
Competing interests: The authors declare no conflict of interest.
Provenance and peer review: Not commissioned; externally peer reviewed.
Luther Gwaza1,2, BPharm, MPhil; John Gordon3, PhD; Henrike Potthast4, PhD; Marc Maliepaard5, PhD; Jan Welink5, Hubert Leufkens1,5, PhD; Matthias Stahl6, MD; Alfredo García-Arieta7, PhD
1Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht, The Netherlands
2Medicines Control Authority of Zimbabwe, 106 Baines Avenue, Harare, Zimbabwe
3Division of Biopharmaceutics Evaluation 2, Bureau of Pharmaceutical Sciences, Health Canada, Locator 0201C, 101 Tunney’s Pasture Driveway, Ottawa, ON K1A 0K9, Canada
4Federal Institute of Drugs and Medical Devices, 3 Kurt-Georg-Kiesinger-Allee, DE-53175 Bonn, Germany
5Medicines Evaluation Board, 500 Graadt van Roggenweg, NL-3531 AH Utrecht, The Netherlands
6Group Leader Medicines Assessment Prequalification Team – Medicines, HIS/EMP/RHT, World Health Organization, 20 Avenue Appia, CH-1211 Geneva 27, Switzerland
7División de Farmacología y Evaluación Clínica, Departamento de Medicamentos de Uso Humano, Agencia Española de Medicamentos y Productos Sanitarios, 1 Calle Campezo, Edificio 8, Planta 2 Oeste, ES-28022 Madrid, Spain
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12. Herranz M, Morales-Alcelay S, Corredera-Hernández MT, de la Torre-Alvarado JM, Blázquez-Pérez A, Suárez-Gea ML, et al. Bioequivalence between generic tacrolimus products marketed in Spain by adjusted indirect comparison. Eur J Clin Pharmacol. 2013;69(5):1157-62.
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14. Yu Y, Teerenstra S, Vanmolkot F, Neef C, Burger D, Maliepaard M. Investigation into the interchangeability of generic formulations using immunosuppressants and a broad selection of medicines. Eur J Clin Pharmacol. 2015;71(8):979-90.
15. World Health Organization. WHO Expert Committee on Pharmaceutical Preparations. Multisource (generic) pharmaceutical products: guidelines on registration requirements to establish interchangeability. in WHO Technical Report Series, No. 992. 2015, Annex 7 [homepage on the Internet]. [cited 2016 Apr 11]. Available from: http://apps.who.int/medicinedocs/documents/s21898en/s21898en.pdf
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Author for correspondence: Alfredo García-Arieta, PhD, División de Farmacología y Evaluación Clínica, Subdirección General de Medicamentos de Uso Humano, Agencia Española de Medicamentos y Productos Sanitarios, 1 Calle Campezo, Edificio 8, Planta 2 Oeste, ES-28022 Madrid, Spain |
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Source URL: https://gabi-journal.net/assessment-of-the-interchangeability-between-generics.html
Author byline as per print journal: Niels Eckstein, PhD; Lea Röper, BSc; Bodo Haas, PhD; Henrike Potthast, PhD; Ulrike Hermes, PhD; Christoph Unkrig, MD; Frauke Naumann-Winter, PhD; Harald Enzmann, MD
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Aim: To provide a systematic overview on: i) safety profiles; ii) pharmacokinetic parameters; and iii) regulatory framework of anti-cancer tyrosine kinase inhibitors (TKI). |
Submitted: 7 February 2014; Revised: 13 March 2014; Accepted: 13 March 2014; Published online first: 26 March 2014
Initially, great expectations were associated with these drugs; some were met, others not. Tyrosine kinase inhibitors (TKIs) are a very worthy additional option for physicians in clinical management of certain types and lines of treatment of cancer, see Table 1 for a tabular overview. In haemato-oncology, they are contributing to the tendency of chronificating rather than curing the disease. In contrast, the expectation of a new era of cancer-therapy without or at least substantially less side effects were not fulfilled, TKI have numerous, partly severe side effects eventually entailed with fatal outcome, see Table 2. On the other hand, after evolving of resistance to conventional (cytotoxic) or targeted anti-cancer therapy, TKI serve as additional therapy options in second, third and/or fourth-line therapy regimes according to their approved indications. For instance, Sunitinib is approved after Imatinib resistance formation in gastrointestinal stromal tumours (GIST), and Lapatinib after non-responding to antracycline- or taxane-based chemotherapy in combination with Trastuzumab in HER-2 positive breast cancer. Taken together, TKI are a valuable extension of the cancer drug armamentarium [1, 2].
According to their European birth date during the past decade, these substances successively will be running off-patent within the next years, see Table 1. From a regulatory point of view, this raises the question how marketing authorization applications (MAA) should be filed and especially, how therapeutic equivalence should be established for generic applications. In general, demonstrated bioequivalence (BE) allows generic medicinal products to refer to the efficacy and safety data of the originator medicinal product. It is easy to anticipate, that numerous questions in this regard will arise in the near future.
Aqueous (non-complicated) intravenously applied drug products have a 100% bioavailability directly per definition, thus, no BE studies are required for a MAA of such generic drugs. However, for orally applied drug products, BE with the originator product needs to be shown, which may be done using patients or healthy volunteers in respective in vivo studies or by means of comparative in vitro investigations.
Since decades BE-acceptance criteria for area under the curve (AUC) and, maximum plasma concentration (Cmax) require the 90% confidence intervals being completely within 80–125% (for AUC and Cmax) to assume BE. The acceptance range may be tightened to 90–111% for one or both pharmacokinetic (PK) characteristics according to the European BE-Guideline [3] in the case of narrow therapeutic index drugs (NTID). In cases of class I and III compounds having identified not to have a narrow therapeutic index – specific in vitro dissolution data may substitute for human BE-studies considering also particular requirements on excipients. This concept follows the principles of the biopharmaceutical classification system (BCS) [3].
It is likely that numerous questions in regard to the appropriate data package will arise in the near future including questions on the appropriate study design, on the appropriate study population, nutrition status, single or repeated dose design, appropriate BCS classification of the individual compound or the classification as NTID.
MAA for new generics may be processed via different regulatory authorizations routes, i.e. national procedures in European Member States, decentralized procedures involving several European Member States or centralized procedures for all European Member States. As the latter is an option only for generics for which the originator medicinal products already obtained marketing authorization from a centralized procedure, this option may receive more attention with the increasing number of medicinal products with centralized authorizations that are running off data protection and patent in the next years.
With the intent to enable a consistent approach for these different routes the European Medicines Agency (EMA) issued an initiative to harmonize the data requirements throughout European Member States, i.e. EMA initiated a pro-active programme ‘Product-Specific Bioequivalence – Guidance for Generics’ [4]. EMA defines the objective of this initiative as follows: ‘Product specific guidance for the bioequivalence assessment of immediate release generic formulations should a priori be defined.’ Thus, applicants should be given a clear scientific guidance, how to design BE-studies and, thus, how to file generic applications. This programme includes BCS classifications for drug substances, so that a harmonized view on the BCS classification and consequently the appropriateness of a BCS-based biowaiver approach can be expected for respective products. Furthermore, the guidance provides information on the type of expected data, e.g. appropriate study population (patients or healthy volunteers), mode of administration (fasten or fed), single dose or steady-state design, appropriate dose strength and analytes, the classification as NTID. The first wave of 16 medicinal products is dominated by anti-infectives and TKI. Dasatinib, Erlotinib, Imatinib, Sorafenib and Sunitinib are covered in this first round of harmonization [4].
From a clinician’s point of view regarding drug safety, see Table 2, one could be tempted to assume that all anti-cancer medicinal products including TKI are considered as NTID. However, this is not the case. Different definitions of NTID by different regulatory agencies do exist. US Food and Drug Administration classification of narrow therapeutic ratio:
In contrast to the US, for the EU no list of substances with NTID-designation is available. So far the consideration of a given substance as NTID is mainly based on national traditions. Only for a few medicinal substances, e.g. Ciclosporine, Tacrolimus, a harmonized EU decision was issued by a referral procedure. According to the draft ‘Product-Specific Bioequivalence – Guidance for Generics’ no drug is newly considered as NTID, only Tacrolimus is considered as such based on the previously finalized referral procedure.
According to the European Bioequivalence Guideline [3] clinical considerations are the basis for NTID decisions. Thus, safety and efficacy profile have to be taken into account.
Most conventional cytotoxic medicinal products are given parenterally for a short duration in repeated cycles. They are mostly dosed on an individual basis, e.g. body surface or weight. The recommended dose is normally the maximum tolerated dose (MTD) or close to it.
Marketed TKI drugs are typically given continuously via the oral route and at a flat dose. Although a most effective and durable target saturation is the primary objective for dose development of TKI drugs, it is obvious that for several TKI drugs the recommended dose is the same as the reported MTD, e.g. Bosutinib, Pazopanib, Ponatinib or Sunitinib, see Table 3. The dose-limiting toxicities include grade 3 gastrointestinal and hepatic toxicities, grade 3 skin toxicities, grade 3 fatigue, and grade 3 hypertension. For Sunitinib grade 2 bullous skin toxicity, grade 3 fatigue, and grade 3 hypertension are reported as dose-limiting toxicities. Furthermore, at approximately twice the therapeutic concentration a grade 2 QT-prolongation is expected (Summary of Product Characteristics Sutent [5]).
From a clinical point of view there are arguments for consideration as an NTID for selective TKI which are elucidated for the example of Sunitinib: The dose of 50 mg/d is the recommended dose for renal cell carcinoma and the MTD at the same time. The documented adverse events (AE) and adverse drug reactions (ADR) are serious, and toxicity may be difficult to control due to long half-life of parent compound and main metabolite (40–60 h and 80–110 h, respectively). The described toxicity induces a high probability of dose reductions with the intent to reduce exposure. The patient safety may be impaired in case of an exchange between originator and generic medicinal product following dose reduction: dose reductions of 12.5 mg represent a 25% and 33% decrease from the recommended dose for renal cell carcinoma and neuroendocrine tumours of pancreatic origin, respectively. In case of exchange of the originator for a generic drug the AUC from the reduced dose of the generic may be nearly the same as the AUC from the normal dose of the originator if normal acceptance criteria for BE (90% CI for AUC and Cmax 80–125%) are applied.
From a safety point of view it should be mentioned that chronic exposure to a dose that was identified as the maximum tolerable dose in a short-term study may render the tolerable short-term toxicity into intolerable long-term toxicity.
Dasatinib, Nilotinib and Bosutinib – CML (chronic myeloid leukaemia) – TKI with different safety profiles from a regulatory point of view and availability of second generation TKI
In general TKI are well tolerated in clinical practice, particularly, if compared with the toxicity of cytostatic drugs normally used in oncology. Often side effects are only mild (grade 2 and lower) and occur early in the treatment course. Frequently they last only some days or weeks and resolve spontaneously. Moreover, even if drug-related toxicity requires drug discontinuation, re-exposition is often successful and permanent dose reduction is rarely necessary.
The advent of Imatinib in 2001 has dramatically changed the prognosis in patients with chronic myeloid leukaemia (CML): The five-year survival rate of patients with chronic phase CML improved from approximately 20% in the pre-TKI era to more than 90% [6]. In those patients who achieve a stable cytogenetic response with Imatinib overall survival is reported with 95.2% at 8 years in the literature and thus does not differ statistically significantly from that of the general population [7]. Imatinib is still the most common TKI modality used as a front-line therapy in CML across the world. However, due to the occurrence of Imatinib resistance and intolerance, second generation TKI as Dasatinib, Nilotinib and Bosutinib have been developed. In non-clinical models they are 30 to 300 times more potent than Imatinib and can inhibit most Imatinib-resistant BCR-ABL mutations (EPARs for Imatinib, Dasatinib and Nilotinib [4]). Comparable with the experience in anti-infective drugs, multidrug-resistant BCR/ABL mutations occurs which preclude further use of the approved TKI. For example, patients with T315I mutation respond only on treatment with third generation TKI Ponatinib, which was specifically designed as a treatment option for these populations.
TKI indicated in CML have some side effects in common as myelosuppression, gastrointestinal complaints, rash, fatigue, headache and peripheral and periorbital oedema; however, intensity varies significantly between the different products. Other AE are peculiar of each drug: Imatinib has been uncommonly associated with severe heart failure, while Nilotinib is associated with QT prolongation, pancreatitis, increased rate of cardiovascular events, and occurrence of peripheral arterial occlusive disease (PAOD). Dasatinib may cause pleural, pericardial and peritoneal effusions; additionally interaction with platelet function is discussed to explain higher rates of gastrointestinal bleeding observed in clinical practice. Bosutinib is associated with significant gastrointestinal toxicity (diarrhea) and hepatotoxicity. Serious AE observed with Ponatinib are an alarming high rate of arterial thrombosis, and cardiovascular events as well as hepatotoxicity.
Differences in the safety profiles of these TKI seems to be at least partially explained by the additional inhibition of other signalling pathways apart BCR-ABL [c-Kit, Src family kinases, platelet-derived growth factor receptors (PDGFR), and others].
However, it should be kept in mind that TKI treatment of CML has to be administered lifelong and knowledge about potential long-term risks and efficacy, especially for the second generation TKI Dasatinib, Nilotinib and Bosutinib, is still limited. Whether risks associated with Ponatinib treatment can be tolerated is currently under discussion again.
Not only from a regulatory perspective careful attention on recommended risk minimization measures as defined in the product information is at the end essential to avoid treatment complications that may completely jeopardize the sought treatment success.
The availability of at least five TKI approved for the treatment for CML and the emergence of drug resistance and intolerance have induced a lively and complex debate on the best strategy to optimize TKI treatment.
Currently, CML treatment is ruled by the paradigm that patients with newly diagnosed CML who respond rapidly to initial treatment with a TKI and who do not develop severe intolerance against TKI should continue TKI therapy lifelong. On the other hand, long-term follow up of patients treated in the pivotal trials for Imatinib, Dasatinib and Nilotinib has shown that a relevant proportion of these patients not only achieved complete cytogenetic response but also sustaining reductions in BCR-ABL transcripts below the lower level of quantification (‘complete molecular response’). Stability of BCR-ABL absence over years in these patients has led to speculations that these patients are cured of CML.
However, can treatment be discontinued safely in patients without evidence for minimal residual disease? Results from two studies (STIM; TWISTER) [8, 9] indicate that if TKI (Imatinib) is discontinued, more than half are expected to relapse within one year. At two years post-discontinuation, 47% of patients in TWISTER were still relapse free and remained off therapy. Those with molecular relapse responded to re-treatment, but patients may not attain the same degree of response upon re-treatment, which illustrates the potential risks of treatment discontinuation approach. As data available is derived from relatively small studies and follow-up is limited, larger studies are needed (and planned) to determine further the safety of such strategies. Thus, current CML treatment guidelines still recommend lifelong therapy with TKI.
Other open topics in the scientific discussions on TKI treatment in CML reflect the question, whether a more rapid and deeper molecular response observed for second generation TKI like Dasatinib and Nilotinib is clinically relevant and indicates a better prognosis. In this context high dose treatment (‘MTD approach’) or sequential therapy with different TKI to lower development of resistance are under discussion.
The outstanding progress made in this area of therapy is best illustrated by the fact that since approval of Imatinib the ‘gold standard’ endpoint ‘overall survival’ is no longer sufficiently discriminative for clinical trials in patients with CML under TKI; surrogate marker as ‘complete cytogenetic response’ or ‘major molecular response’ have been validated and are now accepted as efficacy correlate by regulatory agencies.
The orphan regulation aims at fostering drug development for serious or life-threatening diseases with a prevalence of less than five in 10,000 people in the EU. A sponsor may apply for orphan designation any time prior to an application for marketing authorization (usually even before clinical development). The orphan drug status then needs to be confirmed during the marketing authorization procedure. The most important incentive of the regulation is 10-year market exclusivity for an orphan medicinal product with respect to similar medicinal products. Neither EMA nor EU Member States can authorize a product, which is regarded similar with respect to chemical structure and mode of action and therapeutic indication. Generics, by definition, fulfil all of these criteria.
Imatinib is the paradigm of targeted therapy with its target, the Philadelphia chromosome, occurring in two rare forms of cancer, CML and acute lymphatic leukaemia (ALL), which remain rare in spite of recent advances for treatment. Other cancers, e.g. renal cell carcinoma, was recently reported to exceed the prevalence threshold of five in 10,000 people so that no further orphan designations are expected.
In addition to the incentive of the above-mentioned 10-year market exclusivity intended by the European orphan regulation [10], there maybe a probably unintended additional incentive. Special circumstances are conceivable under which the market exclusivity granted for orphan products may exclude marketing authorization of a generic product. These special circumstances first occurred when the orphan drug Tasigna (Nilotinib) was assessed as ‘similar’ to Glivec (Imatinib). Glivec was first authorized in the EU in 2003. The Committee for Medicinal Products for Human Use (CHMP) gave a positive opinion on its benefit-risk balance, the Committee for Orphan Medicinal Products (COMP) confirmed the significant benefit and so Glivec got the most important incentive for the development of medicines for orphan diseases – the market exclusivity. Under the condition of the European orphan drug regulation no medicinal product ‘similar’ to Glivec would get marketing authorization for ten years – unless the similar product had superior efficacy or safety or the market authorization holder (MAH) of the protected product gives consent to the marketing of the similar product.
Several years after marketing authorization of Glivec was granted, similarity assessment of Tasigna concluded that Tasigna was a similar product to Glivec and the market exclusivity of Glivec would therefore be prohibitive for the authorization of Tasigna. In the context of a similarity assessment, three characteristics of a given drug are decisive:
In the first step of Tasigna marketing authorization, this was not problematic, because Tasigna was first authorized in second line after first-line therapy with Glivec. However, with the extension of indications to first-line treatment of CML, Tasigna was authorized only with the consent of the MAH of Glivec (not surprisingly, as both medicines are products of Novartis). The COMP confirmed a significant benefit and thus Tasigna received its ten own year market exclusivity beginning with the commission decision in 2007.
When data protection and orphan market exclusivity expired for Glivec generic Imatinib products to the reference product Glivec were submitted. There was, however, the previous regulatory decision that Glivec and Tasigna are similar products – including the assessment of Imatinib and Nilotinib as similar active substances based on their chemical structure and pharmacological mechanism. An authorization of a generic Imatinib product to the reference product Glivec would therefore not be granted if it violated the 10-year market exclusivity of Tasigna, which began in 2007.
It is safe to assume that the European orphan legislation was never meant to preclude the authorization of generics after the data protection and the ten years orphan protection of the reference product had expired. And it also seems that this was not a deliberate abuse of a complicated legal and regulatory situation by Novartis but rather unintended. If that had been a wicked, albeit brilliant, marketing-driven strategy, the exact alignment of the indications of Glivec and Tasigna would have effectively prevented any Imatinib generics for many years. As the indications of Tasigna and Glivec overlap for the majority of patients but are not identical, a marketing authorization for Imatinib generics restricted to the indications not granted for Tasigna became possible. This is why the indications of generic Imatinib products are different from the indications of the reference product Glivec.
Sometimes the question is raised, whether dose-regimes for pivotal phase III studies (derived from early phases of clinical development) are the right ones. Especially with Erlotinib, where different dose regimes are recommended for different tumour types and toxicity is high, the question is raised: is there a minimal effective dose (MED) in epidermal growth factor receptor (EGFR)-mutated tumours below recommended dosage (or do patients indeed have to be titrated until MTD is reached)? In this regard, dose limiting toxicities (DLT) do not have to be the same for different tumour types or even in one tumour entity for all patients, see Table 3.
Regarding Erlotinib (apart from case reports) currently one publication is available, trying to bridge in vitro evidence directly with patient data [11]. This article is pointing to the fact that the MED of Erlotinib might in fact be below the recommended dose of 100 mg (pancreatic carcinoma) and 150 mg non-small cell lung cancer (NSCLC), respectively. The rationale of this study is: ‘The usual clinical dose of Gefitinib (250 mg/day) is only one third of its MTD, while the dose of Erlotinib (150 mg/day) is at its MTD. In NSCLC cell lines both TKI have similar micromolar (μM) inhibitory concentrations.’ Therefore, the authors investigated whether Erlotinib when administered at only 25 mg/day can inhibit the mutated form of the EGFR in NSCLC. Apart from similar in vitro-IC50-values, blood concentrations of both drugs differ remarkably (by a factor of more than 5):
Csteady state (Gefitinib at 250 mg/day) = 0.5 μM
Csteady state (Erlotinib at 150 mg/day) ≥ 2.5 μM
These values were derived from early phase clinical development programmes of the respective drugs [12, 13].
The authors conclude: ‘In NSCLC cell lines, Gefitinib and Erlotinib have similar inhibitory profiles. In patients with NSCLC and EGFR activating mutations, a dose of Erlotinib 25 mg/day (equivalent to Gefitinib 250 mg/day) leads to impressive response rates and progression free survival similar to the growing experience with the approved doses of Gefitinib (250 mg/day) and Erlotinib (150 mg/day). Identifying prospectively the lowest, clinically active dose ranges of Erlotinib and Gefitinib will help further personalize care for patients with tumours harbouring EGFR mutations.’ Unfortunately, this study is limited in evidence: it is basically an in vitro study correlated with data from only seven patients. Thus, no answer on what is the MED of Erlotinib can be given by now.
A decade ago, TKI were introduced into clinical anti-cancer therapy. At first sight, the molecular mechanism of action appears to comprise only a targeted approach in blocking tyrosine kinases. However, this should not be misleading; numerous closely interconnected signalling pathways are involved and the complexity of TKI molecular mechanism is far from being understood completely. For clinicians, TKI are a worthy new modality of tumour-therapy amending classical cytotoxic regimes. TKI are of substantial benefit in terms of efficacy with a tolerable safety profile. However, long-term safety issues might not be fully elucidated at present and, thus, cannot be finally judged upon. Throughout the next years, many of these substances will run off-patent. Thus, regulatory guidance will be required for instance on whether certain substances like Sunitinib fulfil the criteria of a narrow therapeutic index drug. Apart from that, most TKI are orally administered, thereby raising the question whether BCS-based biowaiver can apply. In addition, design and requirements of BE-studies will be an issue in the EMA-initiative of product specific guidance on anti-cancer TKI.
The support of Mr Andreas Duda is gratefully acknowledged. This review article was supported by intramural funding of the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM).
All authors filed the manuscript, Dr Niels Eckstein and Ms Lea Röper performed a systematic search on clinical PK-parameter.
The opinions mentioned throughout the manuscript are personal views of the authors and do not reflect an official position of the Federal Institute of Drugs and Medical Devices or an EMA-committee or working party, respectively.
Competing interests: The authors declare that they have no competing interests.
Provenance and peer review: Not commissioned; externally peer reviewed.
Lea Röper, BSc
Bodo Haas, PhD
Henrike Potthast, PhD
Ulrike Hermes, MD
Christoph Unkrig, MD
Frauke Naumann-Winter, PhD
Harald Enzmann, MD
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Author for correspondence: Niels Eckstein, PhD, Federal Institute of Drugs and Medical Devices, 3 Kurt-Georg-Kiesinger-Allee, DE-53175 Bonn, Germany |
Disclosure of Conflict of Interest Statement is available upon request.
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