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Activity Number: 606
Type: Contributed
Date/Time: Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #313120 View Presentation
Title: Detecting Treatment Pathway Interaction in Small Clinical Studies
Author(s): Jia Kang*+
Companies: Merck
Keywords: biomarker ; pathway analysis ; pGx
Abstract:

Emerging evidences in the literature suggest the importance of identifying genetic variants that demonstrate significant interaction with drug treatment, in achieving personalized medicine. Traditionally, single genes are often tested for suitability as PD biomarkers. However, pathways are more biologically meaningful units of cellular response to drug treatments, and provide more insights to drugs' mechanism of action than single genes. A natural question that arises, therefore, is whether the interaction between treatment and genes can be established at the pathway level.

Challenges in studying the interaction between treatment and pathway, however, include (1)statistical methods in inferring pathway x treatment interaction are not very well established.(2) biomarker clinical studies are often small in sample size, and not well powered to detect the interaction term.

In this study, we compared several widely used methods to our proposed method in detecting pathway treatment interaction, with the emphasis of small sample size. Through simulations and clinical trial data, we demonstrate the superiority of proposed method to the existing methods in both power and type I error.


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