DocumentCode :
1186649
Title :
Heuristic design of cancer chemotherapies
Author :
Villasana, Minaya ; Ochoa, Gabriela
Author_Institution :
Dept. de Computo Cientifico y Estadistica, Univ. Simon Bolivar, Caracas, Venezuela
Volume :
8
Issue :
6
fYear :
2004
Firstpage :
513
Lastpage :
521
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; drug delivery systems; optimal control; simulated annealing; tumours; cancer chemotherapies; cycle phase specificity; drug schedules; heuristic search methods; immune system; optimal control problem; optimisation; simulated annealing; single cytotoxic agent; tumor growth; Cancer; Drugs; Evolutionary computation; Immune system; Mathematical model; Neoplasms; Optimization methods; Protocols; Search methods; Simulated annealing;
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/TEVC.2004.834154
Filename :
1369244
Link To Document :
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