All Times EDT
Keywords: Bayesian Statistics, Drug development, Innovation
Bayesian statistics have gained an extensive interest in modern clinical research due to its simple probabilistic interpretation. Bayesian methods have the capability of combining the disparate sources of information in terms of “prior” while maintaining reasonable traditional frequentist characteristics. It helps to borrow information strategically under different heterogeneity (e.g., different disease subgroups, different regions etc.). This is particularly useful in planning and executing successful global clinical trials. The combined information may provide enough justification for smaller or shorter clinical studies without sacrificing the goal of evidence-based medicine. Moreover, Bayesian statistics provides mathematically robust ways of combining multiple measures of interest in a trial (e.g., benefit-risk assessment). Recent regulatory guidelines also reflect the usefulness and challenges for using Bayesian methods.
This panel will discuss the opportunities and challenges of using Bayesian statistics in drug development. It will focus on different areas of application of Bayesian statistics in clinical trial. The panel members are:
1. Satrajit Roychoudhury, Pfizer Inc 2. James Travis, CDER, FDA 3. Robert Beckman, Georgetown University