DESCRIPTION:

Mathematical oncologists apply mathematical and computational modeling approaches to every aspect of cancer biology, from tumor initiation to malignant spread and treatment response.    Using data-driven computational models is a powerful and practical way to investigate the therapeutic potential of novel combinations of different strategies for clinical cancer treatment.  This talk will showcase a suite of mathematical models designed to better understand how specific tumor mutations affect the immune system and ultimately impact the efficacy of small-molecule inhibitors and immunotherapy.  Combined with existing and newly generated experimental data, these mathematical models are poised to improve the ability to select promising drugs for clinical trials and reduce the time and costs associated with transitioning novel therapeutic approaches from “equations to bench to bedside.”

LEARNING OBJECTIVES

At the conclusion of this activity, participants will be able to:

• Understand the role of mathematical modeling in oncology

Recognize the potential of math-clinic collaborations to improve cancer therapeutics