title: Model-based drug development: the road to quantitative pharmacology.
abstract: High development costs and low success rates in bringing new medicines to the market demand more efficient and effective approaches. Identified by the FDA as a valuable prognostic tool for fulfilling such a demand, model-based drug development is a mathematical and statistical approach that constructs, validates, and utilizes disease models, drug exposure-response models, and pharmacometric models to facilitate drug development. Quantitative pharmacology is a discipline that learns and confirms the key characteristics of new molecular entities in a quantitative manner, with goal of providing explicit, reproducible, and predictive evidence for optimizing drug development plans and enabling critical decision making. Model-based drug development serves as an integral part of quantitative pharmacology. This work reviews the general concept, basic elements, and evolving role of model-based drug development in quantitative pharmacology. Two case studies are presented to illustrate how the model-based drug development approach can facilitate knowledge management and decision making during drug development. The case studies also highlight the organizational learning that comes through implementation of quantitative pharmacology as a discipline. Finally, the prospects of quantitative pharmacology as an emerging discipline are discussed. Advances in this discipline will require continued collaboration between academia, industry and regulatory agencies.
authors.affiliation: Bristol Myers-Squibb, Princeton, NJ, USA.
authors.forename: Liping
authors.initials: L
authors.lastname: Zhang
authors.forename: Vikram
authors.initials: V
authors.lastname: Sinha
authors.forename: S Thomas
authors.initials: ST
authors.lastname: Forgue
authors.forename: Sophie
authors.initials: S
authors.lastname: Callies
authors.forename: Lan
authors.initials: L
authors.lastname: Ni
authors.forename: Richard
authors.initials: R
authors.lastname: Peck
authors.forename: Sandra R B
authors.initials: SR
authors.lastname: Allerheiligen
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000964:Antimetabolites, Antineoplastic / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use; D015415:Biomarkers / Q000032:analysis / Q000378:metabolism; D002986:Clinical Trials as Topic / Q000379:methods / Q000706:statistics & numerical data; D003198:Computer Simulation; D003657:Decision Making; D003841:Deoxycytidine / Q000008:administration & dosage / Q000031:analogs & derivatives / Q000493:pharmacokinetics / Q000627:therapeutic use; D004305:Dose-Response Relationship, Drug; D004345:Drug Industry / Q000379:methods* / Q000706:statistics & numerical data / Q000639:trends; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015675:Osteocalcin / Q000097:blood; D015663:Osteoporosis, Postmenopausal / Q000097:blood / Q000188:drug therapy; D010600:Pharmacology / Q000379:methods* / Q000706:statistics & numerical data / Q000639:trends; D020849:Raloxifene Hydrochloride / Q000008:administration & dosage / Q000493:pharmacokinetics; D020845:Selective Estrogen Receptor Modulators / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use; D016896:Treatment Outcome; D000093542:Gemcitabine
chemical_list: D000964:Antimetabolites, Antineoplastic; D015415:Biomarkers; D020845:Selective Estrogen Receptor Modulators; D003841:Deoxycytidine; D015675:Osteocalcin; D020849:Raloxifene Hydrochloride; D000093542:Gemcitabine