Systems Mapping: A Computational Tool for Personalized Medicine
Guifang Fu, Jingyuan Liu, Jiangtao Luo, Zhong Wang, Yaqun Wang, Ningtao Wang, Rongling Wu · 2014
Personalized medicine has emerged as a promising approach to designing and developing new drugs for disease interventions based on the individual characteristics of each patient. Because the true worth of personalized medicine heavily relies on our understanding of how patients’ unique molecular and genetic profile makes them susceptible to a certain disease, an increasing body of study has been conducted to identify specific genes and their interactions that contribute to interpersonal variability in drug response. However, many of these studies focus on simple statistical associations between genes and physiological variables that describe drug efficacy or drug toxicity without integrating the mechanistic basis of drug reactions in a patient’s body. A novel model for mapping genes through design principles of biological systems can enhance the elucidation of the genetic architecture for drug response. This model, called systems mapping, incorporates a group of differential equations to quantify the main, epistatic, or pleiotropic effects of genes on biochemical pathways in drug response. In this chapter, we describe a general framework of systems mapping applied to gene mapping for drug response. We pinpoint that systems mapping should provide a computational tool for pharmacogenetic or pharmacogenomic research toward personalized medicine.