Principled Approaches for Quantifying Probability of Success in Clinical Trials

• Activity Number: 660
• Type: Contributed
• Date/Time: Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Suvajit Samanta*+ and Devan Mehrotra and Robin Mogg and Feng Liu and Gang Jia and Yang Song and Weili He and Jared Lunceford
• Companies: Merck Research Laboratories and Merck Research Laboratories and Merck Research Laboratories and University of North Carolina at Chapel Hill and Merck Research Laboratories and Merck and Merck and Merck Research Laboratories
• Keywords: POS ; Clinical Trial ; Go/No Go

Abstract

During the past two decades, approximately 90% of the compounds entering phase I clinical trials have subsequently failed due to inadequate safety, tolerability or efficacy. Potential reasons for failure include (i) suboptimal modeling of the drug mechanism or exposure-response association, and (ii) inadequate assessment of "probability of success" (POS), the latter resulting in less informed GO/NO GO decisions at one or more stages of development. In this easy-to-follow presentation, we will articulate simple but highly effective statistical approaches to enable a more rigorous assessment of POS. The cornerstone of the proposed innovative methods is the principled use of modeling and simulation based on all available information, with proper accounting for uncertainty in critical assumptions. A case study will be used to illustrate the immediate utility of the new methods in clinical trial settings.