Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success
SAUT, Oliver
Institut de Mathématiques de Bordeaux [IMB]
Modélisation Mathématique pour l'Oncologie [MONC]
See more >
Institut de Mathématiques de Bordeaux [IMB]
Modélisation Mathématique pour l'Oncologie [MONC]
SAUT, Oliver
Institut de Mathématiques de Bordeaux [IMB]
Modélisation Mathématique pour l'Oncologie [MONC]
< Reduce
Institut de Mathématiques de Bordeaux [IMB]
Modélisation Mathématique pour l'Oncologie [MONC]
Language
en
Article de revue
This item was published in
Annals of Biomedical Engineering. 2016-07-06, vol. 44, n° 9
Springer Verlag
English Abstract
Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing ...Read more >
Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncol- ogy. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrat- ing their application as well as the current gap between pre- clinical and clinical applications. We conclude with a discus- sion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology.Read less <
English Keywords
Mathematical modeling
Cancer
Cancer screening
Computational modeling
Numerical modeling
Agent-based modeling
Predictive oncology
Epidemiology
Origin
Hal imported