MOGA-Based Multi-drug Optimisation for Cancer Chemotherapy

Saleh Algoul; Muhammad Alam; Kazi Sakib; Alamgir Hossain; Azim Majumder

doi:10.1007/978-3-642-19914-1_19

MOGA-Based Multi-drug Optimisation for Cancer Chemotherapy

Saleh Algoul, Muhammad Alam, Kazi Sakib, Alamgir Hossain, Azim Majumder

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4 Citations (Scopus)

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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.

Original language	English
Pages (from-to)	133-140
Journal	Advances in Intelligent and Soft Computing
Volume	93
DOIs	https://doi.org/10.1007/978-3-642-19914-1_19
Publication status	Published - 2011

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10.1007/978-3-642-19914-1_19

Algoul MOGASubmitted manuscript, 336 KB

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title = "MOGA-Based Multi-drug Optimisation for Cancer Chemotherapy",

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{\textquoteright}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.",

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note = "From the book for the 5th International Conference on Practical Applications of Computational Biology \& Bioinformatics (PACBB 2011).Rocha, Miguel P. et al (eds) ISBN: 9783642199134 DOI: 10.1007/978-3-642-19914-1",

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AU - Algoul, Saleh

AU - Alam, Muhammad

AU - Sakib, Kazi

AU - Hossain, Alamgir

AU - Majumder, Azim

N1 - From the book for the 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011).Rocha, Miguel P. et al (eds) ISBN: 9783642199134 DOI: 10.1007/978-3-642-19914-1

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Y1 - 2011

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AB - 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.

UR - https://www.scopus.com/pages/publications/80052960167

U2 - 10.1007/978-3-642-19914-1_19

DO - 10.1007/978-3-642-19914-1_19

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SP - 133

EP - 140

JO - Advances in Intelligent and Soft Computing

JF - Advances in Intelligent and Soft Computing

ER -

MOGA-Based Multi-drug Optimisation for Cancer Chemotherapy

Abstract

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