MOGA-based multi-drug optimisation for cancer chemotherapy

S. Algoul; M. S. Alam; K. Sakib; M. A. Hossain; M. A.A. Majumder

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

MOGA-based multi-drug optimisation for cancer chemotherapy

S. Algoul^*
, M. S. Alam
, K. Sakib
, M. A. Hossain
, M. A.A. Majumder

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

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
Title of host publication	5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011)
Editors	Miguel Rocha, Juan Corchado Rodriguez, Florentino Fdez-Riverola, Alfonso Valencia
Pages	133-140
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-19914-1_19
State	Published - 2011
Externally published	Yes

Publication series

Name	Advances in Intelligent and Soft Computing
Volume	93
ISSN (Print)	1867-5662

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

General Computer Science

Access to Document

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

Cite this

Algoul, S., Alam, M. S., Sakib, K., Hossain, M. A., & Majumder, M. A. A. (2011). MOGA-based multi-drug optimisation for cancer chemotherapy. In M. Rocha, J. Corchado Rodriguez, F. Fdez-Riverola, & A. Valencia (Eds.), 5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011) (pp. 133-140). (Advances in Intelligent and Soft Computing; Vol. 93). https://doi.org/10.1007/978-3-642-19914-1_19

Algoul, S. ; Alam, M. S. ; Sakib, K. et al. / MOGA-based multi-drug optimisation for cancer chemotherapy. 5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011). editor / Miguel Rocha ; Juan Corchado Rodriguez ; Florentino Fdez-Riverola ; Alfonso Valencia. 2011. pp. 133-140 (Advances in Intelligent and Soft Computing).

@inproceedings{a90ab7c7b86142e29e5a223e7780ee54,

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'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.",

author = "S. Algoul and Alam, \{M. S.\} and K. Sakib and Hossain, \{M. A.\} and Majumder, \{M. A.A.\}",

year = "2011",

doi = "10.1007/978-3-642-19914-1\_19",

language = "English",

isbn = "9783642199134",

series = "Advances in Intelligent and Soft Computing",

pages = "133--140",

editor = "Miguel Rocha and \{Corchado Rodriguez\}, Juan and Florentino Fdez-Riverola and Alfonso Valencia",

booktitle = "5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011)",

}

Algoul, S, Alam, MS, Sakib, K, Hossain, MA & Majumder, MAA 2011, MOGA-based multi-drug optimisation for cancer chemotherapy. in M Rocha, J Corchado Rodriguez, F Fdez-Riverola & A Valencia (eds), 5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011). Advances in Intelligent and Soft Computing, vol. 93, pp. 133-140. https://doi.org/10.1007/978-3-642-19914-1_19

MOGA-based multi-drug optimisation for cancer chemotherapy. / Algoul, S.; Alam, M. S.; Sakib, K. et al.
5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011). ed. / Miguel Rocha; Juan Corchado Rodriguez; Florentino Fdez-Riverola; Alfonso Valencia. 2011. p. 133-140 (Advances in Intelligent and Soft Computing; Vol. 93).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - MOGA-based multi-drug optimisation for cancer chemotherapy

AU - Algoul, S.

AU - Alam, M. S.

AU - Sakib, K.

AU - Hossain, M. A.

AU - Majumder, M. A.A.

PY - 2011

Y1 - 2011

N2 - 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.

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

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

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AN - SCOPUS:80052960167

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BT - 5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011)

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ER -

Algoul S, Alam MS, Sakib K, Hossain MA, Majumder MAA. MOGA-based multi-drug optimisation for cancer chemotherapy. In Rocha M, Corchado Rodriguez J, Fdez-Riverola F, Valencia A, editors, 5th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB 2011). 2011. p. 133-140. (Advances in Intelligent and Soft Computing). doi: 10.1007/978-3-642-19914-1_19

MOGA-based multi-drug optimisation for cancer chemotherapy

Abstract

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UN SDGs

ASJC Scopus subject areas

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