Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success
hal.structure.identifier | University of Texas at Austin [Austin] | |
dc.contributor.author | YANKEELOV, Thomas E. | |
hal.structure.identifier | University of Chicago | |
dc.contributor.author | AN, Gary | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Modélisation Mathématique pour l'Oncologie [MONC] | |
dc.contributor.author | SAUT, Oliver | |
hal.structure.identifier | Washington University in Saint Louis [WUSTL] | |
dc.contributor.author | GENIN, Guy M. | |
hal.structure.identifier | Fred Hutchinson Cancer Research Center [Seattle] [FHCRC] | |
dc.contributor.author | LUEBECK, E. Georg | |
hal.structure.identifier | Johns Hopkins University [JHU] | |
dc.contributor.author | POPEL, Aleksander S. | |
hal.structure.identifier | Roche Pharma Research and Early Development [Basel] [pRED] | |
dc.contributor.author | RIBBA, Benjamin | |
hal.structure.identifier | MedImmune | |
dc.contributor.author | VICINI, Paolo | |
hal.structure.identifier | Wake Forest University | |
dc.contributor.author | ZHOU, Xiaobo | |
hal.structure.identifier | Vanderbilt University [Nashville] | |
dc.contributor.author | WEIS, Jared A. | |
hal.structure.identifier | State University of New York [SUNY] | |
dc.contributor.author | YE, Kaiming | |
dc.date.accessioned | 2024-04-04T03:13:06Z | |
dc.date.available | 2024-04-04T03:13:06Z | |
dc.date.issued | 2016-07-06 | |
dc.identifier.issn | 0090-6964 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/193927 | |
dc.description.abstractEn | 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. | |
dc.language.iso | en | |
dc.publisher | Springer Verlag | |
dc.subject.en | Mathematical modeling | |
dc.subject.en | Cancer | |
dc.subject.en | Cancer screening | |
dc.subject.en | Computational modeling | |
dc.subject.en | Numerical modeling | |
dc.subject.en | Agent-based modeling | |
dc.subject.en | Predictive oncology | |
dc.subject.en | Epidemiology | |
dc.title.en | Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success | |
dc.type | Article de revue | |
dc.subject.hal | Informatique [cs]/Modélisation et simulation | |
dc.subject.hal | Sciences du Vivant [q-bio]/Cancer | |
dc.subject.hal | Mathématiques [math]/Equations aux dérivées partielles [math.AP] | |
bordeaux.journal | Annals of Biomedical Engineering | |
bordeaux.volume | 44 | |
bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
bordeaux.issue | 9 | |
bordeaux.institution | Université de Bordeaux | |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.peerReviewed | oui | |
hal.identifier | hal-01396241 | |
hal.version | 1 | |
hal.popular | non | |
hal.audience | Internationale | |
hal.origin.link | https://hal.archives-ouvertes.fr//hal-01396241v1 | |
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