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A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors
by
Yin, Anyue
, Swen, Jesse J.
, Guchelaar, Henk‐Jan
, Moes, Dirk Jan A.R.
, Hasselt, Johan G.C.
in
Cancer
/ Drug resistance
/ Growth models
/ Mathematical models
/ Mutation
/ Ordinary differential equations
/ Review
/ Reviews
/ Simulation
/ Studies
/ Treatment resistance
/ Tumors
2019
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A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors
by
Yin, Anyue
, Swen, Jesse J.
, Guchelaar, Henk‐Jan
, Moes, Dirk Jan A.R.
, Hasselt, Johan G.C.
in
Cancer
/ Drug resistance
/ Growth models
/ Mathematical models
/ Mutation
/ Ordinary differential equations
/ Review
/ Reviews
/ Simulation
/ Studies
/ Treatment resistance
/ Tumors
2019
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Do you wish to request the book?
A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors
by
Yin, Anyue
, Swen, Jesse J.
, Guchelaar, Henk‐Jan
, Moes, Dirk Jan A.R.
, Hasselt, Johan G.C.
in
Cancer
/ Drug resistance
/ Growth models
/ Mathematical models
/ Mutation
/ Ordinary differential equations
/ Review
/ Reviews
/ Simulation
/ Studies
/ Treatment resistance
/ Tumors
2019
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A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors
Journal Article
A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors
2019
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Overview
Increasing knowledge of intertumor heterogeneity, intratumor heterogeneity, and cancer evolution has improved the understanding of anticancer treatment resistance. A better characterization of cancer evolution and subsequent use of this knowledge for personalized treatment would increase the chance to overcome cancer treatment resistance. Model‐based approaches may help achieve this goal. In this review, we comprehensively summarized mathematical models of tumor dynamics for solid tumors and of drug resistance evolution. Models displayed by ordinary differential equations, algebraic equations, and partial differential equations for characterizing tumor burden dynamics are introduced and discussed. As for tumor resistance evolution, stochastic and deterministic models are introduced and discussed. The results may facilitate a novel model‐based analysis on anticancer treatment response and the occurrence of resistance, which incorporates both tumor dynamics and resistance evolution. The opportunities of a model‐based approach as discussed in this review can be of great benefit for future optimizing and personalizing anticancer treatment.
Publisher
John Wiley & Sons, Inc,John Wiley and Sons Inc,Wiley
Subject
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