Noise and Signaling in Cancer Systems Pharmacology

Cellular behavior is collectively controlled the spatiotemporal dynamics of biochemical signaling networks, which are often well-described chemical kinetics-based differential equation models. Our prior work based on such models helped reveal design principles of these systems and how they may be interfaced with traditional pharmacokinetics models to help inform drug dosing regimens. However, gene expression and many other biochemical reactions are noisy processes, which can cause significant cell-to-cell variability in signal transduction, and as a result heterogeneity in cell fates such as response to a drug. Therefore we will also highlight recent and ongoing work that integrates single cell experimental data with stochastic approaches to modeling biochemical signaling networks which can give insight into how noisy signaling controls phenotypic divergence.