• 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