AMS Special Seminar: Dr. Angela Jarrett (University of Texas- Austin) @ Maryland 109

Title: Guiding clinical and preclinical investigations of breast cancer with mathematical modeling and analyses
Abstract: One of the great challenges for cancer treatment is the inability to optimize therapy. Without a reasonable mathematical framework, our ability to select treatment regimens for the individual patient is fundamentally limited to trial and error. Presented here are examples of data-driven, integrated experimental-mathematical approaches to studying breast cancer’s response to therapy for both pre-clinical and clinical investigations. The preclinical model, consisting of ODEs, connects various experiments for an in vivo mouse system to better understand the interactions of the immune response and targeted therapy for breast cancer. The clinical model is a 3D PDE system for predicting tumor response to neoadjuvant therapy using patient-specific data that lays the groundwork for optimizing chemotherapeutic dosing and scheduling. In both examples, the results of uncertainty and sensitivity analyses are discussed to show how they can be used to generate experimentally testable hypotheses, narrow the scope for experimental investigations, and evolve mathematical models. Additionally, multi-scale models are proposed that bridge the gap between in vitro and in vivo experiments to step towards clinical translation.