  While the use of combination therapy is increasing in prevalence for cancer
treatment, it is often difficult to predict the exact interactions between
different treatment forms, and their synergistic/antagonistic effects on
patient health and therapy outcome. In this research, a system of ordinary
differential equations is constructed to model nonlinear dynamics between tumor
cells, immune cells, and three forms of therapy: chemotherapy, immunotherapy,
and radiotherapy. This model is then used to generate optimized combination
therapy plans using optimal control theory. In-silico experiments are conducted
to simulate the response of the patient model to various treatment plans. This
is the first mathematical model in current literature to introduce radiotherapy
as an option alongside immuno- and chemotherapy, permitting more flexible and
effective treatment plans that reflect modern therapeutic approaches.
