ADAPTIVE GRADIENT METHOD FOR THE OPTIMAL CONTROL OF AN ANTICANCER THERAPY MODEL

Abstract

Cancer is a set of diseases whose mechanisms of emergence and growth are not completely known. Mathematical and computational models aim to contribute to a better understanding of these mechanisms in tumor dynamics. They can also be used to analyze the impact of anticancer therapeutic protocols. In this sense, we investigate a mathematical model of tumor growth dynamics from the optimal control point of view. We apply the Switching-Time-Variation method to solve the control problem and modify its implementation in order to reduce computational time. Our results show that the execution time of the adaptive method is significantly shorter, and optimal controls for the observed scenario are of the bang-bang type with administration by maximum tolerated dose. The analysis also suggests that the application of another drug capable of acting on resistant tumor cells is required.