Cited by 373Pharmaceutical studies and practicesStatistical Methods in Clinical TrialsPharmacogenetics and Drug Metabolism

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Good Practices in Model‐Informed Drug Discovery and Development: Practice, Application, and Documentation

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EFPIA MID3 Workgroup, Marshall, SF, Burghaus, R, Cosson, V, Cheung, SYA, Chenel, M, DellaPasqua, O, Frey, N, Hamrén, B, Harnisch, L, Ivanow, F, Kerbusch, T, Lippert, J, Milligan, PA, Rohou, S, Staab, A, Steimer, JL, Tornøe, C, Visser, SAG·2016·CPT: Pharmacometrics & Systems Pharmacology

DOI 10.1002/psp4.12049PMC PMC4809625

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Abstract

This document was developed to enable greater consistency in the practice, application, and documentation of Model‐Informed Drug Discovery and Development (MID3) across the pharmaceutical industry. A collection of “good practice” recommendations are assembled here in order to minimize the heterogeneity in both the quality and content of MID3 implementation and documentation. The three major objectives of this white paper are to: i) inform company decision makers how the strategic integration of MID3 can benefit R&D efficiency; ii) provide MID3 analysts with sufficient material to enhance the planning, rigor, and consistency of the application of MID3; and iii) provide regulatory authorities with substrate to develop MID3 related and/or MID3 enabled guidelines.

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Figure 1 Range of application types spanning discovery, development, regulatory assessment, and life‐cycle management. The Shading indicates areas for which we have presented case studies which can be found in the supplemental material.CC BY-NC-ND · PubMed Central

Figure 2 Model Informed Drug Discovery and Development (MID3): genesis of terminology.CC BY-NC-ND · PubMed Central

Figure 3 MID3: a quantitative framework for prediction and extrapolation centered on knowledge and inference generated from integrated models of compound, mechanism, and disease level data aimed at improving the quality, efficiency, and cost‐effectiveness of decision‐making. The colored boxes represent essential components of the “Learn and Confirm Cycle”. The arrows represent processes that link these components.CC BY-NC-ND · PubMed Central

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Authors: Workgroup, E. M., Marshall, S., Burghaus, R., Cosson, V, Cheung, S., Chenel, M., DellaPasqua, O., Frey, N., Hamrén, B., Harnisch, L., Ivanow, F., Kerbusch, T., Lippert, J., Milligan, P., Rohou, S., Staab, A., Steimer, J., Tornøe, C., & Visser, S.
Affiliations: Pfizer (United Kingdom) (GB)
F. Hoffmann-La Roche AG (CH)
AstraZeneca (United Kingdom) (GB)
GlaxoSmithKline (United Kingdom) (GB)
Clinical Pharmacology Modelling & Simulation GlaxoSmithKline R&D Ltd Uxbridge UK
Janssen (United Kingdom) (GB)
MSD (Netherlands) (NL)
Pharmacometrics Pfizer Ltd Sandwich UK
Global Regulatory Affairs & Policy AstraZeneca Paris France
Novartis (Switzerland) (CH)
Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
Quantitative Pharmacology & Pharmacometrics Merck & Co Kenilworth USA
Corresponding author: Marshall, SF
ORCID: Burghaus, R
Cosson, V
Cheung, SYA
Chenel, M
Frey, N
Hamrén, B
Harnisch, L
Kerbusch, T
Lippert, J
Venue: CPT: Pharmacometrics & Systems Pharmacology
Publisher: Wiley
Published: 2016-03
Volume: 5
Issue: 3
Pages: 93-122
ISSN: 2163-8306 (ISSN-L)
DOI: 10.1002/psp4.12049
PMC: PMC4809625
OpenAlex: W2181278642
Cited by: 373
References: 82
Citations by year: 2026: 26 · 2025: 44 · 2024: 37 · 2023: 36 · 2022: 32 · 2021: 51 · 2020: 38 · 2019: 40 · 2018: 33 · 2017: 22 · 2016: 12
FWCI: 22.58
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by-nc
creativecommons.org/licenses/by-nc/4.0/ (vor, 13 d)
Locations: CPT Pharmacometrics & Systems Pharmacology (publishedVersion, cc-by-nc)
Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
PubMed Central (publishedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
Keywords: good practice recommendations, pharmacokinetic-pharmacodynamic modeling, R&D efficiency, regulatory guidelines, pharmaceutical industry
MeSH terms: Documentation, Technology, Pharmaceutical, Drug Design, Guidelines as Topic

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Good Practices in Model‐Informed Drug Discovery and Development: Practice, Application, and Documentation

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