Quantifying the Propagation of Resistance to Chemotherapy in Cancer

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Drug resistance represents a major obstacle to improving the overall response and survival of cancer patients. While most tumors initially respond well to drug therapies, the majority will relapse at a certain point following treatment. Therapeutic failure may be attributed to intrinsic tumor heterogeneity prior to therapy or induced tumor heterogeneity after initiation of therapy. This project aims at developing mathematical models for studying the emergence and the spatial and temporal propagation of single or multidrug resistance under drug-specific treatment protocols. The tools developed in this project will provide a foundation for designing personalized therapy that can be adjusted based on the dynamics of the resistance to chemotherapy. The project involves training of graduate students as well as curriculum and outreach initiatives.The PI will focus on developing, simulating, and analyzing new mathematical models for describing the dynamics of drug resistance in cancer, as mediated by intratumoral heterogeneity. Biologically-based mathematical models will include: hybrid discrete-continuous models, integro-differential equations, stochastic models, and partial-differential equations. The project opens new research opportunities that are guided by PI's established collaborations with clinicians and experimentalists. The focus of this funded project is on the mathematical aspects of the study. A successful completion of this project will provide us with a wide range of mathematical approaches for future translational research in experimental and clinical studies.