Evidence map›Paper›PMID 39875758›Full record

ArticlePharmaceutical research2025

Leveraging Model Master Files for Long-Acting Injectables.

Yuqing Gong, Robert Hopefl, Tonglei Li, Andrew C Hooker, Daniela Amaral Silva, Khondoker Alam, Murray Ducharme, Rebecca Moody, Pratik Saha, Andrew Babiskin

Erratum issuedAbstract read
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In one paragraph

Article in Pharmaceutical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

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, , MD, 20993, USA.
Robert Hopefl *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, , MD, 20993, USA.
Tonglei LiDepartment of Industrial and Physical Pharmacy, Purdue University, West Lafayette, IN, USA.
Andrew C HookerDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Daniela Amaral SilvaSimulations Plus, Inc, Lancaster, CA, USA.
Khondoker AlamDivision 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, , MD, 20993, USA.
Murray DucharmeLearn and Confirm Inc, St. Laurent, QC, Canada.
Rebecca MoodyOffice of Pharmaceutical Quality, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Pratik SahaGlaxoSmithKline, Collegeville, PA, USA.
Andrew BabiskinDivision 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, , MD, 20993, USA. Andrew.Babiskin@fda.hhs.gov.ORCID http://orcid.org/0000-0001-9968-0197

Funding

FDA HHS U18 FD007054U.S. Food and Drug Administration 75F40119C10018U.S. Food and Drug Administration 75F40121C00133U.S. Food and Drug Administration 75F40122C00139U.S. Food and Drug Administration HHSF223201710015CU.S. Food and Drug Administration U18FD007054
6 · The paper itself

Abstract

The U.S. Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG) hosted a public workshop on May 2-3, 2024, titled "Considerations and Potential Regulatory Applications for a Model Master File". The workshop aimed to discuss the application of the Model Master File (MMF) concept in regulatory submissions that contain model integrated evidence (MIE), improving model sharing, model standardization, regulatory consistency, and regulatory efficiency. On Day 1, there was a session dedicated to MMF applications for long-acting injectables (LAIs). This perspective summarizes presentations, panel discussion, and small group discussion for the potential applications of MMFs in LAI product development, including case studies and potential situations in which MMFs can support regulatory submissions. The scientific presentations discussed the application of MMFs in mechanistic physiologically based pharmacokinetic (PBPK), multiphysics simulation, and population pharmacokinetics (popPK) models, as well as the potential utility of a model-integrated bioequivalence (MI-BE) framework. Additionally, challenges and considerations of implementing MMFs for LAIs were discussed in the panel and small groups. The anticipated benefits of MMFs are recognized among model developers, industries, and regulators.

Indexed as

Delayed-Action PreparationsModels, BiologicalComputer SimulationDrug ApprovalHumansInjectionsTherapeutic EquivalencyUnited StatesUnited States Food and Drug AdministrationDelayed-Action Preparationslong acting injectablesmodel integrated evidencemodel master file

Identifiers

PMID39875758
PMCPMC12159082

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Registered trials

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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.