Statistical tests for detecting reference product change in biosimilar studies
Category: Review Article
95 total, 1 today
Author byline as per print journal: Jiayin Zheng1, PhD; Peijin Wang2, MS; Yixin Wang3, PhD; Shein-Chung Chow2, PhD
For the biosimilarity assessment between a test product and a reference product, the US Food and Drug Administration (FDA) recommends a stepwise approach for obtaining totality-of-the-evidence in support of regulatory approval of the submission. The stepwise approach starts
with conducting an analytical similarity assessment of certain critical quality attributes that are relevant to clinical outcome; however, potential drift in mean response and/or variability associated with the reference product over time may be observed. When there is a drift, it is of interest to determine which lots should be used for analytical similarity assessments. In this article, statistical tests for detecting possible drifts in mean and/or variability are derived. In summary, a statistical method is proposed that performs well to detect drift in the mean/variability of biological products while controlling false positive rates and maintain desired true positive rates even when the number of lots is large.
Submitted: 23 August 2022; Revised: 3 January 2023; Accepted: 12 January 2023; Published online first: 25 January 2023
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This manuscript has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record.