TY - JOUR
T1 - MOGA-Based Multi-drug Optimisation for Cancer Chemotherapy
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
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
U2 - 10.1007/978-3-642-19914-1_19
DO - 10.1007/978-3-642-19914-1_19
M3 - Article
SN - 2194-5357
VL - 93
SP - 133
EP - 140
JO - Advances in Intelligent and Soft Computing
JF - Advances in Intelligent and Soft Computing
ER -
