Modeling Resistance in Oncolytic Viral Therapy

Drug resistance is a common phenomenon in the treatment of cancer. As with other cancer therapies, treatment failure due to resistance also occurs for the oncolytic viral therapy (OVT). In this talk, we introduce a simple deterministic model of tumor-virus interaction to investigate OVT resistance. The free oncolytic viruses are modeled explicitly as one compartment and the tumor cells are classified as either susceptible, resistant, or infected. Since there is a time delay from the initial viral infection to the time when infected cells are able to infect other tumor cells, we also study a model of delay differential equations. The deterministic model framework is then applied to formulate models of continuous-time Markov chains and stochastic differential equations. Numerical simulations are performed for these models using plausible parameter values from the literature. We end the talk with biological conclusions and outline possible future directions.