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

  • Meeting Report
  • Best Practices for Utilizing Modeling Approaches to Support Generic Product Development: A Series of Workshop Summary Reports
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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.

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Acknowledgements

The authors thank Drs. Sameersingh Raney (FDA), James Polli (CRCG), Anna Schwendeman (CRCG), Vishalakshi Krishnan (CRCG), Ms. Dana Hammell (CRCG), and Ms. Jennifer Dick (CRCG), for helping organize the workshop. We would also like to thank all the speakers and panelists who participated in the workshop. The authors thank Dr. Sara Lomonaco for manuscript editing assistance.

Funding

This workshop was supported by the Food and Drug Administration (FDA) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award U18FD007054 totaling $1,000,000 with 100 percent funded by FDA/HHS. A.C. H’s work was supported by FDA contracts: HHSF223201710015C, 75F40119C10018. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement, by FDA/HHS, or the U.S. Government. The others’ work reported in this article is not funded/sponsored.

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Author notes

  1. Lanyan Fang and Yuqing Gong contributed equally.

Authors and Affiliations

  1. 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

    Lanyan Fang, Yuqing Gong & Liang Zhao

  2. Department of Pharmacy, Uppsala University, Uppsala, Sweden

    Andrew C. Hooker

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

    Viera Lukacova

  4. Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK

    Amin Rostami-Hodjegan

  5. Certara Inc., Princeton, New Jersey, USA

    Amin Rostami-Hodjegan & Mark Sale

  6. 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

    Stella Grosser

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

    Rebeka Jereb

  8. NDA Partners LLC., A ProPharma Group Company, Washington, District of Columbia, USA

    Carl Peck

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

    Rada Savic & Carl Peck

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  1. Lanyan Fang
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  11. Liang Zhao
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Contributions

LF, YG, ACH, VL, ARH, CP, and LZ drafted and reviewed the manuscript. All other authors reviewed the manuscript

Corresponding author

Correspondence to Liang Zhao.

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Conflict of Interest

The authors declare no competing interests.

Disclosure

The opinions expressed in this article are those of the authors and do not necessarily represent the views or policies of their affiliated organizations/agencies. ACH is a co-founder and an advisor to the pharmaceutical consulting company Pharmetheus AB. ARH was co-founder of a PBPK Modeling and Simulation tool that is commercially distributed by Certara Inc. and is a part-time employee and shareholder of that company. VL is an employee and holds stock of Simulations Plus, Inc. MS is an employee of Certara Inc. and an author of the pyDarwin python Package.

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Fang, L., Gong, Y., Hooker, A.C. et al. The Role of Model Master Files for Sharing, Acceptance, and Communication with FDA. AAPS J 26, 28 (2024). https://doi.org/10.1208/s12248-024-00897-8

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  • DOI: https://doi.org/10.1208/s12248-024-00897-8

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