Mathematical modeling of cancer radiovirotherapy

David Dingli, Matthew D. Cascino, Krešimir Josić, Stephen J. Russell, Željko Bajzer

Research output: Contribution to journalArticlepeer-review

83 Scopus citations


Cancer virotherapy represents a dynamical system that requires mathematical modeling for complete understanding of the outcomes. The combination of virotherapy with radiation (radiovirotherapy) has been recently shown to successfully eliminate tumors when virotherapy alone failed. However, it introduces a new level of complexity. We have developed a mathematical model, based on population dynamics, that captures the essential elements of radiovirotherapy. The existence of corresponding equilibrium points related to complete cure, partial cure, and therapy failure is proved and discussed. The parameters of the model were estimated by fitting to experimental data. By using simulations we analyzed the influence of parameters that describe the interaction between virus and tumor cell on the outcome of the therapy. Furthermore, we evaluated relevant therapeutic scenarios for radiovirotherapy, and offered elements for optimization.

Original languageEnglish (US)
Pages (from-to)55-78
Number of pages24
JournalMathematical Biosciences
Issue number1
StatePublished - 2006


  • Cancer
  • Gene therapy
  • Mathematical model
  • Radioiodide
  • Therapy optimization
  • Virotherapy

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics


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