Basic stochastic model for tumor virotherapy

Math Biosci Eng. 2020 Jun 17;17(4):4271-4294. doi: 10.3934/mbe.2020236.

Abstract

The complexity of oncolytic virotherapy arises from many factors. In this study, we incorporate environmental noise and stochastic effects to our basic deterministic model and propose a stochastic model for viral therapy in terms of Ito stochastic differential equations. We conduct a detailed analysis of the model using boundary methods. We find two combined parameters, one describes possibilities of eradicating tumors and one is an increasing function of the viral burst size, which serve as thresholds to classify asymptotical dynamics of the model solution paths. We show there are three ergodic invariant probability measures which correspond to equilibrium states of the deterministic model, and extra possibility to eradicate tumor due to strong variance of tumor growth rate and medium viral burst size. Numerical analysis demonstrates several typical solution paths with biological explanations. In addition, we provide some medical interpretations and implications.

Keywords: Ito stochastic differential equation; ergodic invariant probability measure; viral burst size; virotherapy.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computer Simulation
  • Humans
  • Models, Biological
  • Neoplasms* / therapy
  • Oncolytic Virotherapy*
  • Stochastic Processes