Applications of Bayesian Statistics in Clinical Trials: Part 1
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*Thomas A. Louis, Johns Hopkins University 


The use of Bayesian statistics has conspicuously increased in clinical trial research because it is ideally suited to adapting to information that accrues during a trial, potentially resulting in smaller, shorter, and more informative trials and for allowing patients to receive better treatment during the course of a trial. In this course we will hear from experts in academia, industry and the FDA on how to design, analyze, and interpret a Bayesian clinical trial in various settings, and how the resulting design can be used in the development of a novel health care product. We will hear the advantages and challenges of using Bayesian methodologies, followed by several case studies. Four speakers: Prof. Tom Louis, Dr. Andrew Mugglin, Dr. Scott Berry and Dr. Pablo Bonangelino will present examples of the use of Bayesian methods in drug and medical device clinical trials. Both regulatory and industry perspectives will be given.