title: Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort.
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.
authors.affiliation: 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.
authors.forename: Franziska
authors.initials: F
authors.lastname: Michor
authors.affiliation: Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Electronic address: bealk@mskcc.org.
authors.forename: Kathryn
authors.initials: K
authors.lastname: Beal
mesh_terms: D000970:Antineoplastic Agents / Q000008:administration & dosage*; D002986:Clinical Trials as Topic; D016503:Drug Delivery Systems; D019008:Drug Resistance, Neoplasm; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy* / Q000473:pathology*
chemical_list: D000970:Antineoplastic Agents