Model-based control of cancer progression subject to drug-resistance

This study deals with the planning of anti-cancer therapy in mice with drug-resistance using mathematical modeling and optimal control. By making use of experimental data in order to develop our mathematical models, we herein propose a promising methodology by which cancer progression in mice with resistance to docetaxel, a widely-used anti-cancer drug, can be controlled. We leverage experimental findings on the reduced fitness of drug-resistant cells, in terms of their ability to compete for nutrients with the sensitive cells, in order to control total cancer growth; during therapy, growth of sensitive cells is inhibited, however during a drug-free period the sensitive cells have an advantage and prevail. Using optimal control, we demonstrate that the optimal planning of the frequency and magnitude of treatment interruptions is key to the control of cancer progression in subjects with resistance and should be further investigated in an experimental setting.