Bayesian Approaches for Using Real-World Evidence for Regulatory Decision Making

• Activity Number: 439 - Role of External Evidence in Drug Development: Current Practices and Future Perspectives
• Type: Topic Contributed
• Date/Time: Thursday, August 6, 2020 : 10:00 AM to 11:50 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Gary L Rosner* and Chenguang Wang
• Companies: Johns Hopkins University and Johns Hopkins University
• Keywords: Bayesian models; Clinical registry; Clinical trials; Exchangeability

Abstract

There is great interest in what is called “real-world evidence” (RWE), particularly in the development of new therapeutic or diagnostic medical products. Uses of this information depend on the user’s perspective. Some wish to use RWE to provide context for evaluating the results of clinical trials. Others wish to combine real-world data with data from similarly treated or diagnosed patients enrolled in clinical trials to reduce the size of the trial and shorten the trial’s duration. Still others are interested in developing a method that will allow them to provide synthetic control cohorts to the biomedical community for use as “historical controls.” In this talk, we will look at several Bayesian approaches one might apply when incorporating real-world data for regulatory decision-making. Our goal is to see how Bayesian methods can be applied to better characterize the intent-to-treat or intent-to-diagnose patients and to leverage RWE in the clinical trial’s design and analysis.