Heuristic Design of Cancer Chemotherapies

Abstract

A methodology using heuristic search methods is proposed for optimizing cancer chemotherapies with drugs acting on a specific phase of the cell cycle. Specifically, two evolutionary algorithms, and a simulated annealing method are considered. The methodology relies on an underlying mathematical model for tumor growth that includes cycle phase specificity, and multiple applications of a single cytotoxic agent. The goal is to determine effective protocols for administering the agent, so that the tumor is eradicated, while the immune system remains above a given threshold. Results confirm that modern heuristic methods are a good choice for optimizing complex systems. The three algorithms considered produced effective solutions, and provided drug schedules suitable for practice, although some methods excelled others in performance. A discussion of comparative results is presented.