Periodic chemotherapy dose schedule optimization using genetic algorithm

Alam, Nadia, Sultana, Munira, Alam, Muhammad, Al-Mamun, Mohammad and Hossain, Alamgir (2013) Periodic chemotherapy dose schedule optimization using genetic algorithm. In: Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing, 217 . Springer, pp. 503-511. ISBN 978-3-319-00550-8

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Abstract

This paper presents a design method for optimal cancer chemotherapy schedules using genetic algorithm (GA). The main objective of chemotherapy is to reduce the number of cancer cells or eradicate completely, if possible, after a predefined time with minimum toxic side effects which is difficult to achieve using conventional clinical methods due to narrow therapeutic indices of chemotherapy drugs. Three drug scheduling schemes are proposed where GA is used to optimize the doses and schedules by satisfying several treatment constraints. Finally, a clinically relevant dose scheme with periodic nature is proposed. Here Martin’s model is used to test the designed treatment schedules and observe cell population, drug concentration and toxicity during the treatment. The number of cancer cells is found zero at the end of the treatment for all three cases with acceptable toxicity. So the proposed design method clearly shows effectiveness in planning chemotherapy schedules.

Item Type:	Book Section
Uncontrolled Keywords:	cancer chemotherapy, drug scheduling, genetic algorithm, mathematical model, optimization
Subjects:	B900 Others in Subjects allied to Medicine G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Becky Skoyles
Date Deposited:	19 Jan 2015 12:28
Last Modified:	12 Oct 2019 22:26
URI:	http://nrl.northumbria.ac.uk/id/eprint/20800

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