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Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Adopting the Model Master File Framework to Enhance Modeling and Simulations Approaches for Regulatory Use.

Lanyan Fang1, Eleftheria Tsakalozou2, Fang Wu2

  • 1Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration (FDA), Silver Spring, MD, USA. lanyan.fang@fda.hhs.gov.

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Keywords:
Model Master File (MMF)Model-Informed Drug Development (MIDD)Model-Integrated Evidence (MIE)drug product developmentregulatory assessment

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Area of Science:

  • Pharmacometrics and Computational Science
  • Drug Regulatory Science
  • Pharmaceutical Development

Background:

  • The pharmaceutical industry increasingly uses modeling and simulation for drug development and regulatory submissions.
  • Regulatory agencies like the FDA are exploring innovative ways to integrate these models into assessments.
  • The Model-Integrated Evidence (MIE) program aims to leverage quantitative models for regulatory decision-making.

Purpose of the Study:

  • To provide an overview of modeling and simulation advancements in drug development and regulatory assessment.
  • To highlight the FDA's initiatives, including the Model-Informed Drug Development (MIDD) and MIE programs.
  • To introduce the concept and regulatory implications of Model Master Files (MMFs).

Main Methods:

  • Review of historical advancements in drug development modeling and simulation.
  • Discussion of FDA programs like MIDD and MIE meetings.
  • Analysis of the Type V Drug Master File (DMF) for Model Master File (MMF) submissions.
  • Summary of discussions from the "Considerations and Potential Regulatory Applications for a Model Master File (MMF)" workshop.

Main Results:

  • The FDA's Type V DMF for MMFs facilitates model-sharing and reusability in drug development.
  • MMFs support MIE programs using diverse quantitative models (PBPK, PPK, CFD).
  • The workshop provided insights into MMF considerations and potential regulatory applications.

Conclusions:

  • Model Master Files (MMFs) reduce resource burdens for pharmaceutical companies adopting modeling and simulation.
  • MMFs enhance consistency and efficiency in regulatory assessments.
  • The adoption of MMFs is expected to promote wider use of advanced modeling and simulation in drug development.