Optimal Control Theory formulation based on maximizing the life expectancy of chemotherapy patients

SPAAM Seminar Series 14/11/24
Title: An Optimal Control Theory formulation that is based on maximizing the life expectancy of cancer chemotherapy patients
Speaker: Byron Tzamarias, University of Warwick (MathSys)

Abstract: We propose a life expectancy payoff (LEP) function for determining optimal cancer treatment by averaging future outcomes weighted by their impacts on life expectancy. These outcomes include successful treatment (tumor elimination), failure to clear the tumor (relapse), and death during treatment, including treatment-related mortality (TRM).
The LEP can be parameterized using data, involving the estimation of risk rates (including mortality) and their dependencies on patient demographics, tumor characteristics, and treatment effects. Developed within a deterministic control theory framework, the LEP employs tumor control probabilities derived from branching processes to account for cell and lineage extinction.
We illustrate the optimization of the LEP using basic tumor growth models, specifically the logistic growth model, with three possible outcomes: tumor elimination (cure), primary tumor relapse, and death during treatment (TRM). This analysis categorizes patients into treatable and untreatable groups, influenced by factors such as patient demographics, tumor size, tumor response, and drug toxicity. For patients in the treatable group, an optimal duration for maximum tolerated dose (MTD) treatment is identified. This duration varies minimally with patient age and is primarily determined by the patient’s susceptibility to drug toxicity and the size of the tumor prior therapy.

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