Computational modeling approaches to studying the dynamics of oncolytic viruses

Oncolytic viruses specifically infect cancer cells, replicate in them, killthem, and spread to further tumor cells. They represent a targeted treatmentapproach that is promising in principle, but consistent success has yet tobe observed. Mathematical models can play an important role in analyzing th...

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Main Author: Dominik Wodarz
Format: Article
Language:English
Published: AIMS Press 2013-03-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2013.10.939
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author Dominik Wodarz
author_facet Dominik Wodarz
author_sort Dominik Wodarz
collection DOAJ
description Oncolytic viruses specifically infect cancer cells, replicate in them, killthem, and spread to further tumor cells. They represent a targeted treatmentapproach that is promising in principle, but consistent success has yet tobe observed. Mathematical models can play an important role in analyzing thedynamics between oncolytic viruses and a growing tumor cell population,providing insights that can be useful for the further development of thistherapy approach. This article reviews different mathematical modelingapproaches ranging from ordinary differential equations to spatiallyexplicit agent-based models. Problems of model robustness are discussed andso are some clinically important insight derived from the models.
format Article
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institution Kabale University
issn 1551-0018
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spelling doaj-art-3f9f23fda5e841c889c11afd95a9e90a2025-01-24T02:26:12ZengAIMS PressMathematical Biosciences and Engineering1551-00182013-03-0110393995710.3934/mbe.2013.10.939Computational modeling approaches to studying the dynamics of oncolytic virusesDominik Wodarz0Department of Ecology and Evolutionary Biology, University of California, 321 Steinhaus Hall, Irvine, CA 92617Oncolytic viruses specifically infect cancer cells, replicate in them, killthem, and spread to further tumor cells. They represent a targeted treatmentapproach that is promising in principle, but consistent success has yet tobe observed. Mathematical models can play an important role in analyzing thedynamics between oncolytic viruses and a growing tumor cell population,providing insights that can be useful for the further development of thistherapy approach. This article reviews different mathematical modelingapproaches ranging from ordinary differential equations to spatiallyexplicit agent-based models. Problems of model robustness are discussed andso are some clinically important insight derived from the models.https://www.aimspress.com/article/doi/10.3934/mbe.2013.10.939therapymathematical modelsoncolytic virusesspatial dynamics.cancerpopulation dynamics
spellingShingle Dominik Wodarz
Computational modeling approaches to studying the dynamics of oncolytic viruses
Mathematical Biosciences and Engineering
therapy
mathematical models
oncolytic viruses
spatial dynamics.
cancer
population dynamics
title Computational modeling approaches to studying the dynamics of oncolytic viruses
title_full Computational modeling approaches to studying the dynamics of oncolytic viruses
title_fullStr Computational modeling approaches to studying the dynamics of oncolytic viruses
title_full_unstemmed Computational modeling approaches to studying the dynamics of oncolytic viruses
title_short Computational modeling approaches to studying the dynamics of oncolytic viruses
title_sort computational modeling approaches to studying the dynamics of oncolytic viruses
topic therapy
mathematical models
oncolytic viruses
spatial dynamics.
cancer
population dynamics
url https://www.aimspress.com/article/doi/10.3934/mbe.2013.10.939
work_keys_str_mv AT dominikwodarz computationalmodelingapproachestostudyingthedynamicsofoncolyticviruses