Evidence map›Paper›PMID 38413548›Full record

ArticleThe AAPS journal2024

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

Lanyan Fang, Yuqing Gong, Andrew C Hooker, Viera Lukacova, Amin Rostami-Hodjegan, Mark Sale, Stella Grosser, Rebeka Jereb, Rada Savic, Carl Peck and 1 more

Abstract read
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In one paragraph

Article in The AAPS journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Best Practices in Physiologically Based Pharmacokinetic (PBPK) Modeling.CPT: pharmacometrics & systems pharmacology · 2026
    Review
  3. Article
  4. Review
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Lanyan Fang *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 *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 HookerDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Viera LukacovaSimulations Plus, Inc., Lancaster, California, USA.
Amin Rostami-HodjeganCentre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.
Mark SaleCertara Inc., Princeton, New Jersey, USA.
Stella GrosserDivision 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 JerebLek Pharmaceuticals d.d., a Sandoz Company, Ljubljana, Slovenia.
Rada SavicDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA.
Carl PeckNDA Partners LLC., A ProPharma Group Company, Washington, District of Columbia, USA.
Liang ZhaoDivision 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.ORCID 0000-0002-0257-9082

Funding

Center for Research on Complex GenericsU18FD007054 · FDA · UNIVERSITY OF MARYLAND BALTIMORE · PI JAMES E POLLI, Anna Schwendeman · 2020 to 2026
$6.8M
FDA HHS U18 FD007054
6 · The paper itself

Abstract

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.

Indexed as

CommunicationDrug DevelopmentComputer SimulationDrugs, GenericUnited StatesUnited States Food and Drug AdministrationDrugs, Generic

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.