Determining optimal chemotherapy schedules using ODE modeling and control

Kung, Shannon
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University of Delaware
Chemotherapy is mostly effective in helping cancer patients but invariably some cells will mutate to become more fit against chemotherapeutic agents. We build upon previous work that focuses on transfecting tumor cells via a delivery virus. The transfected cells then become both chemoresistant and sensitive to ganciclovir, which is an acyclic nucleotide antiviral agent. A positive selection phase of chemotherapy administration and negative selection phase of ganciclovir injection enables a chemoresistant tumor to be eradicated by a bystander effect. The bystander effect occurs when ganciclovir is applied and is strong enough to eradicate the tumor if cell populations and parameters are favorable. An ordinary differential equation model is used to represent the biological phenomena. A control system is developed in computer simulation to find the optimal treatment strategy. We improve upon previous research by modifying the cost function to measure for absolute minimum tumor size and also by incorporating realistic physiological parameters into our models.