This work demonstrates optimal viral burst sizes in reducing tumour load with oncolytic virotherapy, highlighting multiple cell populations.
Oncolytic virotherapy is a cancer treatment that uses replicating viruses to target and kill tumour cells. The interaction between tumour cells and an oncolytic virus can be represented in a mathematical model. In this paper we study the development of some mathematical models and their dynamics. We study the conclusions of various approaches to the modelling, including a system of ordinary differential equations, the dynamical system’s theory, and a predatory-prey model. The study analyses thresholds that enable us to identify solutions of a virus-cell interaction function. We run Hopf bifurcation to classify stable equilibrium points in the function. We also propose a mathematical model on oncolytic virotherapy incorporating multiple cell populations and free viruses. Optimal viral burst sizes to reduce tumour load in the quickest time are obtained. Burst sizes around 25 were found to be optimal, and 3 viral drugs, including a modified HSV and an adenovirus ONYX-015, were presented as the most effective treatments.
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Odhrani et al. (2024) studied this question.
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