TY - JOUR
T1 - Optimum multi-drug regime for compartment model of tumour
T2 - cell-cycle-specific dynamics in the presence of resistance
AU - Panjwani, Bharti
AU - Singh, Vijander
AU - Rani, Asha
AU - Mohan, Vijay
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2021/8
Y1 - 2021/8
N2 - This work is focused on multi-objective optimisation of a multi-drug chemotherapy schedule for cell-cycle-specific cancer treatment under the influence of drug resistance. The acquired drug resistance to chemotherapeutic agents is incorporated into the existing compartmental model of breast cancer. Furthermore, the toxic effect of drugs on healthy cells and overall drug concentration in the patient body are also constrained in the proposed model. The objective is to determine the optimal drug schedule according to the patient’s physiological condition so that the tumour burden is minimised. A multi-objective optimisation algorithm, non-dominated sorting genetic algorithm-II (NSGA-II) is utilised to solve the problem. The obtained results are thoroughly analysed to illustrate the impact of drug resistance on the treatment. The capability of optimised schedules to deal with parametric uncertainty is also analysed. The drug schedules obtained in this work align well with the clinical standards. It is also revealed that the NSGA-II optimised drug schedule with proper rest period between successive dosages yields the minimum cancer load at the end of the treatment.
AB - This work is focused on multi-objective optimisation of a multi-drug chemotherapy schedule for cell-cycle-specific cancer treatment under the influence of drug resistance. The acquired drug resistance to chemotherapeutic agents is incorporated into the existing compartmental model of breast cancer. Furthermore, the toxic effect of drugs on healthy cells and overall drug concentration in the patient body are also constrained in the proposed model. The objective is to determine the optimal drug schedule according to the patient’s physiological condition so that the tumour burden is minimised. A multi-objective optimisation algorithm, non-dominated sorting genetic algorithm-II (NSGA-II) is utilised to solve the problem. The obtained results are thoroughly analysed to illustrate the impact of drug resistance on the treatment. The capability of optimised schedules to deal with parametric uncertainty is also analysed. The drug schedules obtained in this work align well with the clinical standards. It is also revealed that the NSGA-II optimised drug schedule with proper rest period between successive dosages yields the minimum cancer load at the end of the treatment.
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U2 - 10.1007/s10928-021-09749-w
DO - 10.1007/s10928-021-09749-w
M3 - Article
C2 - 33751365
AN - SCOPUS:85103254080
SN - 1567-567X
VL - 48
SP - 543
EP - 562
JO - Journal of Pharmacokinetics and Pharmacodynamics
JF - Journal of Pharmacokinetics and Pharmacodynamics
IS - 4
ER -