Heuristic design of cancer chemotherapies

Citation

Villasana M & Ochoa G (2004) Heuristic design of cancer chemotherapies. IEEE Transactions on Evolutionary Computation, 8 (6), pp. 513-521. https://doi.org/10.1109/TEVC.2004.834154

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.

Keywords
cancer model; cycle-specific chemotherapy; evolution strategies (ESs); evolutionary algorithms (EAs); genetic algorithms (GAs); simulated annealing (SA); singular optimal control

Journal
IEEE Transactions on Evolutionary Computation: Volume 8, Issue 6