All Times EDT
Keywords: Historical Data Borrowing, Bayesian Methods, Clinical Trial Design
Historical data borrowing presents an important opportunity to augment information and improve efficiency for clinical trials in the rare disease areas and other circumstances where enrollment difficulties are encountered. Bayesian trial design provides a natural, coherent and flexible framework to incorporate historical data into late phase clinical trials. While Bayesian historical data borrowing holds great promise, we are facing substantial challenges ranging from assessment of exchangeability between historical and current studies to intensive trial simulation at design stage to harmonization of the chance of erroneous conclusions between frequentist and Bayesian approaches. Hence, brainstorming and experience-sharing have never been more important than today in this area. In this roundtable, we intend to promote discussion among statisticians from industry, academia, and regulatory agencies, on the key statistical issues in Bayesian historical data borrowing and its application in clinical trials. Here are some questions to start the discussion. • What is your biggest challenge / hurdle when you or your company considers use of Bayesian historical data borrowing in clinical trials, especially late phase trials? • What is your experience when you try to explain Bayesian trial design and historical data borrowing to your clinical counterparts and/or product development team? • Bayesian trial design with historical data borrowing usually requires intensive trial simulation to understand trial operating characteristics. What is your experience in this regard (including use of high-performance computing)?