Modeling the Pharmacogenetic Architecture of Drug Response

Abstract Clinical pharmacogenomics, aimed at integrating genomic information with clinical practices to facilitate the prediction of drug response, has recently emerged as a vital area of public health. To make clinical pharmacogenomics a success, we need a comprehensive understanding of how genes singly or interactively affect patients’ response to a particular drug. In this chapter, we review statistical designs for mapping the genetic architecture of drug response using molecular markers. Genes that affect a pharmacological response, their number, genomic distribution, and genetic actions and interactions can be estimated and tested. Functional mapping that integrates genetic mapping with pharmacodynamic and pharmacokinetic machineries of drug response can improve the precision of mapping results and their clinical interpretations. Genome-wide association studies (GWASes), beyond traditional genetic mapping approaches, provide an unprecedented opportunity to chart a complete picture of the genetic control of drug response. The implementation of GWASes by functional mapping leads to the birth of a dynamic model, f GWAS, for studying and characterizing clinical pharmacogenomics toward personalized medicine.