A Predictive Bayesian Approach to the Design and Analysis of Bridging Studies

• Activity Number: 650
• Type: Topic Contributed
• Date/Time: Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): A. Lawrence Gould*+ and Tian Jin and Li Xin Zhang and William W. B. Wang
• Companies: Merck and Shanghai University of Finance and Economics and MSD (Shanghai) Pharma Co. and MSD (Shanghai) Pharma Co.
• Keywords: Bayes ; confidence ; regulatory

Abstract

Pharmaceutical product development culminates in confirmatory trials whose evidence for the product's efficacy and safety supports regulatory approval. Regulatory agencies in countries not included in the confirmatory trials often require confirmation of efficacy and safety in local patients, which may be accomplished by carrying out 'bridging studies' to establish consistency of the effects demonstrated by the original trials. We describe an approach for designing and analyzing 'bridging studies' that fully incorporates the information from the original trials. The approach determines probability contours of joint predictive intervals for treatment effect and response variability, endpoints of treatment effect confidence intervals, or other regions combining estimated treatment effect and variability that are functions of the findings from the original trials, the sample size for the 'bridging study', and possible deviations from complete consistency with the original trials. A 'bridging' study is judged consistent with the original trials if its findings fall within the defined region; regulatory considerations determine the probability levels for the regions.