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Activity Number:
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223
- Clinical Trials: Recent Statistical Advances for Enabling Personalized Medicine
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Type:
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Topic Contributed
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Date/Time:
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Monday, July 31, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #323475
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View Presentation
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Title:
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A Powerful Learn-And-Confirm Pharmacogenomics Methodology for Randomized Clinical Trials
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Author(s):
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Devan Mehrotra* and Qian Guan and Zifang Guo
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Companies:
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Merck & Co. Inc. and North Carolina State University and Merck & Co., Inc.
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Keywords:
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genome-wide association study (GWAS) ;
pharmacogenetics ;
probability of success ;
single nucleotide polymorphism (SNP) ;
winner's curse adjustment
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Abstract:
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In response to the increasing needs of patients/prescribers/payers, pharmaceutical companies continue to seek efficient ways to explore whether a drug under development is suitable for all or only an identifiable subset of patients in the intended target population. Rapid advances in genotyping technologies and falling costs have created opportunities to make this timely exploration a reality. In the first half of this presentation, we will describe a powerful statistical method for discovering potential predictors of drug response via genome-wide association (GWAS) studies in randomized clinical trials. In the second half, we will discuss strategies for confirmation of discoveries, with particular focus on a novel "winner's curse" adjustment applied to relevant parameter estimates obtained from the GWAS analysis in the learning phase. An illustrative example and simulations will be used to reinforce the key points.
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Authors who are presenting talks have a * after their name.
