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All Times EDT

Friday, September 25
Fri, Sep 25, 2:00 PM - 3:15 PM
Virtual
Trial Design and Analysis Considerations in the Product Development for Rare Diseases

Bayesian Probability of Success for Multiple Endpoints (301175)

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*Ethan Mackenzie Alt, University of North Carolina at Chapel Hill 
Joseph Ibrahim, University of North Carolina at Chapel Hill 
Matthew Psioda, University of North Carolina at Chapel Hill 

Keywords: bayesian, probability of success, copula, seemingly unrelated regression, power prior

Given the cost and duration of phase III and phase IV clinical trials, the development of statistical methods for go/no-go decisions is vital. Most methods to compute probability of success are only for single endpoints e.g., Ibrahim et al. (2015). Methods dealing with multiple responses, which are common in clinical trials, are sparse, particularly for non-Gaussian endpoints. In this talk, we present novel techniques to compute probability of success (POS) for multiple endpoints under Gaussian and non-Gaussian assumptions. The tools developed will enable practitioners to compute the likelihood of a successful clinical trial for primary and key secondary endpoints.