Cited by 27Statistical Methods in Clinical TrialsPharmaceutical studies and practicesAnimal testing and alternatives

Translational pharmacokinetic-pharmacodynamic analysis in the pharmaceutical industry: an IQ Consortium PK-PD Discussion Group perspective

Wong, Harvey, Bohnert, Tonika, Damian-Iordache, Valeriu, Gibson, Christopher, Hsu, Cheng-Pang, Krishnatry, Anu Shilpa, Liederer, Bianca M., Lin, Jing +11 more·2017·Drug Discovery Today

Abstract

With inadequate efficacy being the primary cause for the attrition of drug candidates in clinical development, the need to better predict clinical efficacy earlier in the drug development process has increased in importance in the pharmaceutical industry. Here, we review current applications of translational pharmacokinetic-pharmacodynamic (PK-PD) modeling of preclinical data in the pharmaceutical industry, including best practices. Preclinical translational PK-PD modeling has been used in many therapeutic areas and has been impactful to drug development. The role of preclinical translational PK-PD modeling in drug discovery and development will continue to evolve and broaden, given that its broad implementation in the pharmaceutical industry is relatively recent and many opportunities still exist for its further application.

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Crossref · 10.1016/j.drudis.2017.04.015

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Authors
Wong, H., Bohnert, T., Damian-Iordache, V., Gibson, C., Hsu, C.-P., Krishnatry, A. S., Liederer, B. M., Lin, J., Lu, Q., Mettetal, J. T., Mudra, D. R., Nijsen, M. J. M. A., Schroeder, P., Schuck, E., Suryawanshi, S., Trapa, P., Tsai, A., Wang, H., & Wu, F.
Affiliations
  • Genentech (US)
  • Biogen (United States) (US)
  • Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
  • Amgen (United States) (US)
  • GlaxoSmithKline (United States) (US)
  • AstraZeneca (United States) (US)
  • Eli Lilly (United States) (US)
  • AbbVie (United States) (US)
  • Eisai (United States) (US)
  • Bristol-Myers Squibb (United States) (US)
  • Pfizer (United States) (US)
  • Vertex Pharmaceuticals (United States) (US)
Corresponding author
Wong, Harvey
Venue
Drug Discovery Today
Publisher
Elsevier BV
Published
2017-10
Volume
22
Issue
10
Pages
1447-1459
ISSN
1359-6446 (ISSN-L)
OpenAlex
W2611876444
Cited by
27
References
80
Citations by year
2026: 1 · 2025: 6 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 7 · 2020: 5 · 2019: 3
FWCI
0.40
Type
journal article
Language
en
Open access
closed
Locations
  • Drug Discovery Today (publishedVersion)
  • PubMed (publishedVersion)
  • The Novartis Repository (Novartis) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
  • Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
Keywords
drug development, clinical efficacy prediction, drug attrition, drug discovery, preclinical evidence, best practices
MeSH terms
Animals, Drug Industry, Drug Evaluation, Preclinical, Humans, Models, Biological, Drug Discovery

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