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Journal of pharmacokinetics and pharmacodynamics
Oct, 2024;51 (5): 543-555.

Current practices for QSP model assessment: an IQ consortium survey.

Jason R Chan, Richard Allen, Britton Boras, Antonio Cabal, Valeriu Damian, Francis D Gibbons, Abhishek Gulati, Iraj Hosseini, Jeffrey D Kearns, Ryuta Saito, Lourdes Cucurull-Sanchez, Jangir Selimkhanov, Andrew M Stein, Kenichi Umehara, Guanyu Wang, Weirong Wang, Susana Neves-Zaph
Author Information
  1. Jason R Chan: Global PKPD and Pharmacometrics, Eli Lilly and Company, Indianapolis, IN, 46285, USA. jrchan@lilly.com.
  2. Richard Allen: Worldwide Research, Development and Medical, Pfizer Inc. Kendall Square, Cambridge, MA, 02139, USA.
  3. Britton Boras: Worldwide Research, Development and Medical, Pfizer Inc.,, La Jolla, CA, 92121, USA.
  4. Antonio Cabal: Eisai Inc., NJ, Nutley, USA.
  5. Valeriu Damian: GlaxoSmithKline, Collegeville, PA, 19426, USA.
  6. Francis D Gibbons: , Takeda, Cambridge, MA, 02139, USA.
  7. Abhishek Gulati: Merck & Co. Inc., Rahway, NJ, USA.
  8. Iraj Hosseini: Genentech Inc., South San Francisco, CA, 94080, USA.
  9. Jeffrey D Kearns: Novartis Institutes for BioMedical Research, Cambridge, MA, 02139, USA.
  10. Ryuta Saito: Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, Yokohama, Japan.
  11. Lourdes Cucurull-Sanchez: GlaxoSmithKline, Stevenage, Hertfordshire, UK.
  12. Jangir Selimkhanov: Takeda Development Center Americas Inc., San Diego, CA, 92121, USA.
  13. Andrew M Stein: Pharmacometrics, Novartis Institutes of BioMedical Research, Cambridge, MA, USA.
  14. Kenichi Umehara: Roche Pharmaceutical Research and Early Development, Basel, Switzerland.
  15. Guanyu Wang: Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals, Abingdon, Oxfordshire, UK.
  16. Weirong Wang: Clinical Pharmacology and Pharmacometrics, Janssen Research and Development, LLC, Spring House, PA, 19477, USA.
  17. Susana Neves-Zaph: Data and Data Science, Translational Disease Modeling, Sanofi, USA.
PMID: 35953664 DOI: 10.1007/s10928-022-09811-1

Abstract

Quantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions.

Keywords

Decision Making Drug Industry Modeling and Simulation Network Pharmacology

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MeSH Term

Humans
Surveys and Questionnaires
Drug Development
Drug Industry
Network Pharmacology
Models, Biological
Journal Article
Article has an altmetric score of 1

Word Cloud

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