Dynamics of tumor virotherapy: A deterministic and stochastic model approach

Cancer virotherapy is studied in mathematical modeling to improve tumor elimination. Since various oncolytic viruses are used for cancer therapy and virus selection is an important research problem, we, therefore, constructed deterministic and stochastic models of cancer-virus dynamics. We investigated virus characteristic parameter sensitivities using a reproduction ratio. Locally and globally asymptotically stable equilibrium points that are respectively related to therapy failure/partial success and therapy failure were determined. A stochastic system was derived from the deterministic model. Tumor extinction probabilities depending on changing parameter values were investigated. Results suggest that viruses with high infection rates and optimal cytotoxicity are effective for cancer treatment.