Challenges and New Approaches in Identifying Treatment Specific Subgroups That Are Commercially Viable with Binary Outcomes

• Activity Number: 234
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Lin Li*+ and Tobias Guennel and Scott Marshall
• Companies: BioStat Solutions and BioStat Solutions and BioStat Solutions
• Keywords: subgroup identification ; personalized medicine ; multi-marker molecular signature ; composite score

Abstract

As the era of the blockbuster drug is fading, delivering on the promise of personalized medicine has become a focus of the pharmaceutical industry. Both opportunities and challenges for developing analytical strategies exist toward identifying treatment specific subgroups that are commercially viable. This paper will first review the challenges as well as statistical approaches recently proposed for subgroup identification. Then, a multi-marker molecular signature (MMMS) approach for binary treatment response profiles will be presented in particular. The proposed approach identifies and directly tests for a biomarker driven subgroup with enhanced treatment effect, which may be characterized by an improved odds ratio or improved response rate in the treatment group (e.g. positive predictive value). A simulation study is used to demonstrate its capability of confining the search space to a subgroup size that is commercially viable, while maintaining desired statistical properties such as type I error, ultimately resulting in actionable information for use in empirically based decision making.