Model Predictive Control for Optimal Drug Administration of Cancer Chemotherapy

Tumor chemotherapy is one of the most effective ways to improve cancer treatment. However, it is important to design an effective treatment plan that can optimize chemotherapy to reduce its imminent side effects. In this work, a model predictive control strategy for a nonlinear dynamic model of the cancer chemotherapy system is presented. This paper, first deals with parametric uncertainties. The appearance of uncertain parameters in the nonlinear system is proposed to define the negative effect of drug tolerance and delay in the mentioned system. Also, a hybrid cost function is considered for this model, which reduces the length of the treatment period. The simulation results show that the proposed control structure satisfactorily overcomes the negative effect of parameter uncertainties. Cancer cells can be eradicated in a very short period of time by minimizing the amount of drugs using optimal treatment administration.