Applied & Computational Mathematics seminar: Optimizing cancer treatment strategies through mathematical models

Speaker: Anne Talkington, NIST and University at Buffalo

Title:  Optimizing cancer treatment strategies through mathematical models

Abstract:  Despite promising preclinical results, initial successes of therapeutic designs often do not translate into clinical successes. This disparity results from complexity on all scales of a drug’s intended trajectory, from issues with systemic delivery to issues with cellular-level targeting. I will discuss two causes of treatment failure and the corresponding insights gathered from mathematical modeling and simulation. First, I present an 8-compartment physiologically based pharmacokinetic (PBPK) model system for antibody-mediated accelerated drug clearance, a key issue in drug delivery failure. Optimizing model parameters via Latin Hypercube Sampling increases our understanding of the accelerated clearance process. Next, I discuss a complementary dynamical system and agent-based model for tumor-immune interactions. Defining the role of immune checkpoint blockade therapy as an optimal control problem allows us to maximize favorable cellular interactions while minimizing unfavorable cellular interactions by perturbing properties of this therapy. Together, these scenarios underscore the role of optimization in mathematical oncology.

Time:  Friday, October 4 – 1:30pm – 2:30pm
Place:  Exploratory Hall, room 4106 and Zoom