Mathematical simulations of tumor response to cancer treatment

Abstract

Over the past several decades, mathematical modeling techniques have been incorporated into the armamentarium of cancer research. A relatively novel use of mathematics in the realm of oncology is in the process of computer-aided drug discovery--using computer simulations of mathematical models to identify novel drug targets and predict the efficacy of newly developed compounds. In this talk, I will describe a validated hybrid cellular automaton model of tumor growth in a vascularized environment. I will then demonstrate how computer simulations of the mathematical model can be used to study the antitumor activity of several vascular (blood vessel)-targeting compounds and chemotherapeutic agents. Results will be compared to preclinical and clinical trial data, wherever possible. Simulations have revealed that there are inherent limitations in using vascular-targeting drugs as a front-of-the-line cancer treatment. The mathematical model has also been used to identify a novel treatment protocol that, under the assumptions of the model, has more success at limiting cancer growth than standard protocols. Taken together, the analysis herein represents a proof-of-concept that mathematical models can be utilized to determine the antitumor activity of an existing or novel therapeutic compound.