title: Optimizing oncology therapeutics through quantitative translational and clinical pharmacology: challenges and opportunities.
abstract: Despite advances in biomedical research that have deepened our understanding of cancer hallmarks, resulting in the discovery and development of targeted therapies, the success rates of oncology drug development remain low. Opportunities remain for objective dose selection informed by exposure-response understanding to optimize the benefit-risk balance of novel therapies for cancer patients. This review article discusses the principles and applications of modeling and simulation approaches across the lifecycle of development of oncology therapeutics. Illustrative examples are used to convey the value gained from integration of quantitative clinical pharmacology strategies from the preclinical-translational phase through confirmatory clinical evaluation of efficacy and safety.
authors: Clinical Pharmacology, Takeda Pharmaceuticals International Co., Cambridge, Massachusetts, USA.
authors: K
authors: K
authors: Venkatakrishnan
authors: L E
authors: LE
authors: Friberg
authors: D
authors: D
authors: Ouellet
authors: J T
authors: JT
authors: Mettetal
authors: A
authors: A
authors: Stein
authors: I F
authors: IF
authors: Trocóniz
authors: R
authors: R
authors: Bruno
authors: N
authors: N
authors: Mehrotra
authors: J
authors: J
authors: Gobburu
authors: D R
authors: DR
authors: Mould
mesh_terms: D000818:Animals; D000970:Antineoplastic Agents / Q000009:adverse effects / Q000494:pharmacology / Q000627:therapeutic use*; D035843:Biomedical Research / Q000379:methods; D003198:Computer Simulation; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D058990:Molecular Targeted Therapy; D009369:Neoplasms / Q000188:drug therapy* / Q000473:pathology; D010601:Pharmacology, Clinical / Q000379:methods; D057170:Translational Research, Biomedical / Q000379:methods
chemical_list: D000970:Antineoplastic Agents