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Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort.
Michor, Franziska; Beal, Kathryn.
Afiliação
  • Michor F; Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. Electronic address: michor@jimmy.harvard.edu.
  • Beal K; Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Electronic address: bealk@mskcc.org.
Cell ; 163(5): 1059-1063, 2015 Nov 19.
Article em En | MEDLINE | ID: mdl-26590416
ABSTRACT
Drug delivery schedules are key factors in the efficacy of cancer therapies, and mathematical modeling of population dynamics and treatment responses can be applied to identify better drug administration regimes as well as provide mechanistic insights. To capitalize on the promise of this approach, the cancer field must meet the challenges of moving this type of work into clinics.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Biológicos / Neoplasias / Antineoplásicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Cell Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Biológicos / Neoplasias / Antineoplásicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Cell Ano de publicação: 2015 Tipo de documento: Article