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Bayesian design of biosimilars clinical programs involving multiple therapeutic indications

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  • Matthew A. Psioda
  • Kuolung Hu
  • Yang Zhang
  • Jean Pan
  • Joseph G. Ibrahim

Abstract

In this paper, we propose a Bayesian design framework for a biosimilars clinical program that entails conducting concurrent trials in multiple therapeutic indications to establish equivalent efficacy for a proposed biologic compared to a reference biologic in each indication to support approval of the proposed biologic as a biosimilar. Our method facilitates information borrowing across indications through the use of a multivariate normal correlated parameter prior (CPP), which is constructed from easily interpretable hyperparameters that represent direct statements about the equivalence hypotheses to be tested. The CPP accommodates different endpoints and data types across indications (eg, binary and continuous) and can, therefore, be used in a wide context of models without having to modify the data (eg, rescaling) to provide reasonable information‐borrowing properties. We illustrate how one can evaluate the design using Bayesian versions of the type I error rate and power with the objective of determining the sample size required for each indication such that the design has high power to demonstrate equivalent efficacy in each indication, reasonably high power to demonstrate equivalent efficacy simultaneously in all indications (ie, globally), and reasonable type I error control from a Bayesian perspective. We illustrate the method with several examples, including designing biosimilars trials for follicular lymphoma and rheumatoid arthritis using binary and continuous endpoints, respectively.

Suggested Citation

  • Matthew A. Psioda & Kuolung Hu & Yang Zhang & Jean Pan & Joseph G. Ibrahim, 2020. "Bayesian design of biosimilars clinical programs involving multiple therapeutic indications," Biometrics, The International Biometric Society, vol. 76(2), pages 630-642, June.
  • Handle: RePEc:bla:biomet:v:76:y:2020:i:2:p:630-642
    DOI: 10.1111/biom.13163
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    References listed on IDEAS

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    1. Ming-Hui Chen & Joseph G. Ibrahim & Peter Lam & Alan Yu & Yuanye Zhang, 2011. "Bayesian Design of Noninferiority Trials for Medical Devices Using Historical Data," Biometrics, The International Biometric Society, vol. 67(3), pages 1163-1170, September.
    2. Ming-Hui Chen & Joseph G. Ibrahim & Donglin Zeng & Kuolung Hu & Catherine Jia, 2014. "Bayesian design of superiority clinical trials for recurrent events data with applications to bleeding and transfusion events in myelodyplastic syndrome," Biometrics, The International Biometric Society, vol. 70(4), pages 1003-1013, December.
    3. Joseph G. Ibrahim & Ming-Hui Chen & H. Amy Xia & Thomas Liu, 2012. "Bayesian Meta-Experimental Design: Evaluating Cardiovascular Risk in New Antidiabetic Therapies to Treat Type 2 Diabetes," Biometrics, The International Biometric Society, vol. 68(2), pages 578-586, June.
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