Understanding variability in systems pharmacology with application to drug target identification (360G-Wellcome-090433_B_09_Z)

There is currently a big gap between understanding the molecular mechanisms ofbiological networks, identifying drug targets and predicting clinical outcomes of drug treatments in a heterogeneous population of patients. The goal of this project is to narrow this gap by developing a framework that combines mechanistic systems modelling, drug pharmacokinetics and patient variability in a unified fashion. This framework will enable us to make progress in understanding healthy and diseased network physiology, guide us to select optimal drug interventions andquantitatively predict the success of drug therapies on variable patient subpopulations. Specifically, I will develop a quantitative systems pharmacology (QSP) model of a nerve growth factor (NGF) signalling pathway using clinical and molecular data. I will extend the existing model to capture variability in the biological pathway as well as variability between and within individual patients. The model will be used to identify robust drugtargets and to guide aspects of quantitative drug discovery and development for treating paindisorders.