The Optimization of Combination Chemotherapy Schedules in the Presence of Drug Resistance

This paper aims to devise efficient combination chemotherapy schedules that determine the dosages of drugs administered to cancer patients with drug resistance that, as a Gordian knot to cancer chemotherapy, may weaken the efficacy of chemotherapy. To characterize cell growth, we use the existing cell cycle-specific model, in which the mechanism of acquired drug resistance is incorporated. Subsequently, the determination of the optimal chemotherapy schedule for the patients is formulated as a nonlinear optimization problem, with the objective of minimizing not only the quantity of tumor cells but also the posttreatment chemotherapy-induced toxicity. To overcome the difficulty in finding a satisfactory solution to the problem due to its nonlinear nature, we develop a memetic algorithm (MA) with an advanced local search strategy. The efficiency of the proposed MA is validated by comparison with other state-of-the-art methods. In addition, we compare the best found solution to the problem in the presence of drug resistance with that in the absence of drug resistance. The resultant findings reveal that drug resistance is a crucial factor in the determination of chemotherapy schedules.