title: A Review of Modeling Approaches to Predict Drug Response in Clinical Oncology.
abstract: Model-based approaches have emerged as important tools for quantitatively understanding temporal relationships between drug dose, concentration, and effect over the course of treatment, and have now become central to optimal drug development and tailored drug treatment. In oncology, the therapeutic index of a chemotherapeutic drug is typically narrow and a full dose-response relationship is not available, often because of treatment failure. Noting the benefits of model-based approaches and the low therapeutic index of oncology drugs, in recent years, modeling approaches have been increasingly used to streamline oncologic drug development through early identification and quantification of dose-response relationships. With this background, this report reviews publications that used model-based approaches to evaluate drug treatment outcome variables in oncology therapeutics, ranging from tumor size dynamics to tumor/biomarker time courses and survival response.
authors.affiliation: Department of Pharmacology, Yonsei University College of Medicine, Seoul, Korea. kspark@yuhs.ac.
authors.forename: Kyungsoo
authors.initials: K
authors.lastname: Park
mesh_terms: D000970:Antineoplastic Agents / Q000008:administration & dosage* / Q000494:pharmacology; D014408:Biomarkers, Tumor; D004305:Dose-Response Relationship, Drug; D006801:Humans; D008495:Medical Oncology; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy* / Q000473:pathology
chemical_list: D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor
keywords: Model-based approaches; chemotherapeutic drug; drug development; drug treatment