Abstract

In recent years, the use of master protocol design in clinical trials has received much attention. Master protocol design, which includes basket, umbrella, and platform design, has the flexibility of testing multiple therapies in one indication, one therapy for multiple indications or both. In this manner, master protocol design can expedite clinical development of drug products under investigation in a more efficient way. In practice, however, the integrity, quality, and validity of clinical studies utilizing master protocol trial design is a concern due to various issues such as heterogeneity across target patient populations, multiplicity in hypotheses testing, and population drift when using non-concurrent control subjects. In this article, current statistical issues in clinical trials utilizing master protocol design are described and potential solutions are provided. These issues include sample size and power determination, controlling type I error rate, multiplicity, pooled analysis, treatment imbalance/heterogeneity, and population drift. Various approaches have been proposed to control and/or eliminate these issues where many follow Bayesian-based approaches. These practical issues are illustrated through some case studies that demonstrate the implementation of master protocol design within the field of oncology where it is most used and in other therapeutic areas. Some recommendations for resolutions of the practical issues encountered in the case studies are provided.

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