ArticleJournal of theoretical biology2010
ODE models for oncolytic virus dynamics.
Article in Journal of theoretical biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- Next-generation oncolytic virotherapy for lung cancer: bridging innovative vector engineering with clinical immunotherapy.Translational lung cancer research · 2026Review
- The Role of Viral Dynamics and Infectivity in Models of Oncolytic Virotherapy for Tumours with Different Motility.Bulletin of mathematical biology · 2026Article
- CAR T-cell and oncolytic virus dynamics and determinants of combination therapy success for glioblastoma.Mathematical biosciences · 2025Article
- A Mathematical Perspective on the Influence of Allee Effects in Oncolytic Virotherapy.Mathematics (Basel, Switzerland) · 2025Article
- Article
- Agent-Based and Continuum Models for Spatial Dynamics of Infection by Oncolytic Viruses.Bulletin of mathematical biology · 2023Article
- Article
- In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform.BMC bioinformatics · 2020Article
- Article
- Oncolytic virus therapy benefits from control theory.Royal Society open science · 2020Article
- Symmetry structures in dynamic models of biochemical systems.Journal of the Royal Society, Interface · 2020Article
- Basic stochastic model for tumor virotherapy.Mathematical biosciences and engineering : MBE · 2020Article
- Modeling Oncolytic Viral Therapy, Immune Checkpoint Inhibition, and the Complex Dynamics of Innate and Adaptive Immunity in Glioblastoma Treatment.Frontiers in physiology · 2020Article
- Virus-Receptor Interactions and Virus Neutralization: Insights for Oncolytic Virus Development.Oncolytic virotherapy · 2020Review
- Investigating Macrophages Plasticity Following Tumour-Immune Interactions During Oncolytic Therapies.Acta biotheoretica · 2019Article
- Backward Hopf bifurcation in a mathematical model for oncolytic virotherapy with the infection delay and innate immune effects.Journal of biological dynamics · 2019Article
- In vitro and in silico multidimensional modeling of oncolytic tumor virotherapy dynamics.PLoS computational biology · 2019Article
- Kinetic Modeling of Virus Growth in Cells.Microbiology and molecular biology reviews : MMBR · 2018Review
- Imaging, Tracking and Computational Analyses of Virus Entry and Egress with the Cytoskeleton.Viruses · 2018Review
- Developing a Minimally Structured Mathematical Model of Cancer Treatment with Oncolytic Viruses and Dendritic Cell Injections.Computational and mathematical methods in medicine · 2018Article
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2 authors.
Funding
Abstract
Replicating oncolytic viruses are able to infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. This makes them potentially useful in cancer therapy, and a variety of viruses have shown promising results in clinical trials. Nevertheless, consistent success remains elusive and the correlates of success have been the subject of investigation, both from an experimental and a mathematical point of view. Mathematical modeling of oncolytic virus therapy is often limited by the fact that the predicted dynamics depend strongly on particular mathematical terms in the model, the nature of which remains uncertain. We aim to address this issue in the context of ODE modeling, by formulating a general computational framework that is independent of particular mathematical expressions. By analyzing this framework, we find some new insights into the conditions for successful virus therapy. We find that depending on our assumptions about the virus spread, there can be two distinct types of dynamics. In models of the first type (the "fast spread" models), we predict that the viruses can eliminate the tumor if the viral replication rate is sufficiently high. The second type of models is characterized by a suboptimal spread (the "slow spread" models). For such models, the simulated treatment may fail, even for very high viral replication rates. Our methodology can be used to study the dynamics of many biological systems, and thus has implications beyond the study of virus therapy of cancers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.