Statistical Methods and General Principles of Exploratory Biomarker Analysis: Pathway to Personalized Medicine

• Activity Number: 80
• Type: Contributed
• Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Rui Tang*+ and Mike Hale and Jing Huang and Li Chen
• Companies: Amgen and Amgen and Amgen and Amgen Inc.
• Keywords: subgroup analysis ; biomarker analysis ; patient selection ; oncology trial

Abstract

Personalized medicine is a rapidly advancing field that promises greater precision and effectiveness than traditional. Thus, patients could be prescribed the medicine with the greatest chance of benefit and the least likelihood of adverse events. The investigation of predictive and prognostic biomarkers is viewed as a very promising area which could help deliver personalized medicines to patients. As biomarkers become integrated into drug development and clinical trials, tremendous work will need to be dedicated to the biomarker analysis which investigates the role of potential candidate biomarkers in a patient's outcome. We have worked extensively with biomarker scientists to conduct exploratory biomarker analysis for several oncology programs. In this presentation, we will talk about the statistical methods of exploratory biomarker analysis. A case study from phase 2 gastric cancer clinical trial study will be presented. We will present methods, challenges, results and limitations and describe their impact on the phase 3 program. Issues and limitation of these analyses will be indentified and discussed. Experiences with cross-functional collaboration will be shared.