Optimizing adaptive cancer therapy: dynamic programming and evolutionary game theory.

ABSTRACT: Recent clinical trials have shown that adaptive drug therapies can be more efficient than a standard cancer treatment based on a continuous use of maximum tolerated doses (MTD). The adaptive therapy paradigm is not based on a preset schedule; instead, the doses are administered based on the current state of tumour. But the adaptive treatment policies examined so far have been largely ad hoc. We propose a method for systematically optimizing adaptive policies based on an evolutionary game theory model of cancer dynamics. Given a set of treatment objectives, we use the framework of dynamic programming to find the optimal treatment strategies. In particular, we optimize the total drug usage and time to recovery by solving a Hamilton-Jacobi-Bellman equation. We compare MTD-based treatment stra

SUBMITTER: Gluzman M 

PROVIDER: S-EPMC7211445 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature