title: Stochastic modeling of systems mapping in pharmacogenomics.
abstract: As a basis of personalized medicine, pharmacogenetics and pharmacogenomics that aim to study the genetic architecture of drug response critically rely on dynamic modeling of how a drug is absorbed and transported to target tissues where the drug interacts with body molecules to produce drug effects. Systems mapping provides a general framework for integrating systems pharmacology and pharmacogenomics through robust ordinary differential equations. In this chapter, we extend systems mapping to more complex and more heterogeneous structure of drug response by implementing stochastic differential equations (SDE). We argue that SDE-implemented systems mapping provides a computational tool for pharmacogenetic or pharmacogenomic research towards personalized medicine.
authors.affiliation: Department of Biostatistics, Yale University, New Haven, CT 06520, USA. zuoheng.wang@yale.edu
authors.forename: Zuoheng
authors.initials: Z
authors.lastname: Wang
authors.forename: Jiangtao
authors.initials: J
authors.lastname: Luo
authors.forename: Guifang
authors.initials: G
authors.lastname: Fu
authors.forename: Zhong
authors.initials: Z
authors.lastname: Wang
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D003198:Computer Simulation; D004358:Drug Therapy; D014644:Genetic Variation; D006801:Humans; D008954:Models, Biological; D010597:Pharmacogenetics; D010599:Pharmacokinetics; D057285:Precision Medicine; D013269:Stochastic Processes; D049490:Systems Biology