Abstract Details
Activity Number:
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76
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Type:
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Contributed
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Date/Time:
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Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
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Sponsor:
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Biometrics Section
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Abstract - #309704 |
Title:
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Testing Pathway-Dose Interaction in Clinical Studies
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Author(s):
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Jia Kang*+
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Companies:
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Merck
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Keywords:
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Personalized Medicine ;
Treatment Interaction ;
Biomarker
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Abstract:
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Emerging evidences in the literature seem to suggest that virtually every pathway of drug metabolism, transport, and action is susceptible to genetic variation. It is estimated that 20-90% of individual variability is genetically based. Consequently, to identify these genetic variants that show significant interaction with drug treatment is a critical step in achieving the goal of personalized medicine.
Traditionally, treatment x gene interaction is tested at the individual SNP/gene level, however, a limitation of such approach is that genes with moderate but meaningful expression changes may not meet the strict cutoff and alternation of molecular processes may be missed. These are particularly important when studying complex diseases that may be associated with changes of expression of multiple genes. A natural question that arises, therefore, is whether the interaction between treatment and genes can be established at the pathway level.
In this study, we propose a new non-parametric method in assessing the interaction between biological pathways and treatment. We demonstrate the utility of our method via both simulations and real data.
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Authors who are presenting talks have a * after their name.
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