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MOGA-Based Multi-drug Optimisation for Cancer Chemotherapy

  • S. Algoul
  • M. S. Alam
  • K. Sakib
  • M. A. Hossain
  • M. A. A. Majumder
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 93)

Abstract

This paper presents a novel method of multi-drug scheduling using multi-objective genetic algorithm (MOGA) that can find suitable/optimum dosages by trading-off between cell killing and toxic side-effects of chemotherapy treatment. A close-loop control method, namely Integral-Proportional-Derivative (I-PD) is designed to control dosages of drugs to be infused to the patient’s body and MOGA is used to find suitable parameters of the controller. A cell compartments model is developed and used to describe the effects of the drugs on different type of cells, plasma drug concentration and toxic side-effects. Results show that specific drug schedule obtained through the proposed method can reduce the tumour size nearly 100% with relatively lower toxic side-effects.

Keywords

Chemotherapy Drug Drug Schedule Stochastic Universal Sampling Evolutionary Computing Approach Desire Drug Concentration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • S. Algoul
    • 1
  • M. S. Alam
    • 2
  • K. Sakib
    • 1
  • M. A. Hossain
    • 3
  • M. A. A. Majumder
    • 1
  1. 1.University of BradfordBradfordUK
  2. 2.University of DhakaBangladesh
  3. 3.Northumbria UniversityUK

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