Kinetic models of biochemical signaling networks

Abstract

Kinetic models of biochemical signaling networks are a mechanistic description of pharmacodynamics, and thus are potentially well-poised to fill gaps in the drug development pipeline by: (i) allowing putative drugs to be tested via simulations for efficacy and safety before expensive experiments and failed clinical trials; (ii) providing a framework for personalized and precision medicine that incorporates genomic information into a prediction of drug action in an individual; and (iii) interfacing with traditional pharmacokinetic models to yield computable yet mechanistic simulations that can inform drug dosing and frequency. However, biochemical signaling networks are currently incompletely understood on a basic level and are extremely complex compared to traditional applications of kinetic modeling. Herein, we describe current methods used to build such models and highlight strengths and weaknesses of the various approaches, as well as identify areas that need more research to drive the field towards influencing these important potential applications.