The Role of Model Master Files for Sharing, Acceptance, and Communication with FDA.


Journal

The AAPS journal
ISSN: 1550-7416
Titre abrégé: AAPS J
Pays: United States
ID NLM: 101223209

Informations de publication

Date de publication:
27 Feb 2024
Historique:
received: 26 12 2023
accepted: 12 02 2024
medline: 28 2 2024
pubmed: 28 2 2024
entrez: 27 2 2024
Statut: epublish

Résumé

With the evolving role of Model Integrated Evidence (MIE) in generic drug development and regulatory applications, the need for improving Model Sharing, Acceptance, and Communication with the FDA is warranted. Model Master File (MMF) refers to a quantitative model or a modeling platform that has undergone sufficient model Verification & Validation to be recognized as sharable intellectual property that is acceptable for regulatory purposes. MMF provides a framework for regulatorily acceptable modeling practice, which can be used with confidence to support MIE by both the industry and the U.S. Food and Drug Administration (FDA). In 2022, the FDA and the Center for Research on Complex Generics (CRCG) hosted a virtual public workshop to discuss the best practices for utilizing modeling approaches to support generic product development. This report summarizes the presentations and panel discussions of the workshop symposium entitled "Model Sharing, Acceptance, and Communication with the FDA". The symposium and this report serve as a kick-off discussion for further utilities of MMF and best practices of utilizing MMF in drug development and regulatory submissions. The potential advantages of MMFs have garnered acknowledgment from model developers, industries, and the FDA throughout the workshop. To foster a unified comprehension of MMFs and establish best practices for their application, further dialogue and cooperation among stakeholders are imperative. To this end, a subsequent workshop is scheduled for May 2-3, 2024, in Rockville, Maryland, aiming to delve into the practical facets and best practices of MMFs pertinent to regulatory submissions involving modeling and simulation methodologies.

Identifiants

pubmed: 38413548
doi: 10.1208/s12248-024-00897-8
pii: 10.1208/s12248-024-00897-8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

28

Informations de copyright

© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

Références

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Auteurs

Lanyan Fang (L)

Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA.

Yuqing Gong (Y)

Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA.

Andrew C Hooker (AC)

Department of Pharmacy, Uppsala University, Uppsala, Sweden.

Viera Lukacova (V)

Simulations Plus, Inc., Lancaster, California, USA.

Amin Rostami-Hodjegan (A)

Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.
Certara Inc., Princeton, New Jersey, USA.

Mark Sale (M)

Certara Inc., Princeton, New Jersey, USA.

Stella Grosser (S)

Division of Biostatistics VIII, Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.

Rebeka Jereb (R)

Lek Pharmaceuticals d.d., a Sandoz Company, Ljubljana, Slovenia.

Rada Savic (R)

Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA.

Carl Peck (C)

NDA Partners LLC., A ProPharma Group Company, Washington, District of Columbia, USA.
Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA.

Liang Zhao (L)

Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA. Liang.Zhao@fda.hhs.gov.

Classifications MeSH