Multiscale Cancer Modeling

Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of th...

Full description

Saved in:
Bibliographic Details
Published in:Annual review of biomedical engineering 2011-08, Vol.13 (1), p.127-155
Main Authors: Deisboeck, Thomas S, Wang, Zhihui, Macklin, Paul, Cristini, Vittorio
Format: Article
Language:English
Subjects:
Algorithms
cancer systems biology
clinical translation
Computational Biology
Computer Simulation
continuum
discrete
Disease Progression
Humans
hybrid
Models, Biological
Neoplasm Metastasis - pathology
Neoplasms - pathology
Neovascularization, Pathologic
personalized medicine
Precision Medicine - trends
Receptor, Epidermal Growth Factor - metabolism
Systems Biology
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insights in the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community.
ISSN:1523-9829
1545-4274
DOI:10.1146/annurev-bioeng-071910-124729