Tonglei Li, Ph.D. Editor-in-Chief, Pharmaceutical Research
I am pleased to announce the publication of a special issue in May by Pharmaceutical Research that focuses on the FDA's Model Master File (MMF). Most of the articles in this issue are open-access and provide a comprehensive view of the topic, authored by experts from regulatory agencies, industry, and academia. This special issue is particularly dear to my heart, as I am a big fan of modeling and simulation. I hope you find the articles, especially the application cases discussed, to be insightful and forward-looking.
Various modeling and simulation techniques have been utilized in drug development and thereby become part of the drug approval process. Over many years, Pharmacokinetics/Pharmacodynamics (PK/PD) modeling has transformed drug development significantly and is now a fundamental part of every drug application package. These efforts have converged into the so-called Model-Informed Drug Development (MIDD), and the FDA issued draft guidance on this in December 2024. In addition to modeling and simulation, data-driven machine learning and deep learning are poised to revolutionize the drug development process further. In January 2025, the FDA introduced Type V Drug Master Files for MMF submissions to facilitate the sharing and reusability of computational models. An MMF serves as a central source for essential information regarding a model, including its design, algorithm, testing, and intended application targets. This information is crucial for the FDA to assess the model's suitability for drug development. One MMF can be utilized in multiple submissions, thereby reducing redundancy and burden in the regulatory review process.
As computational models become more advanced and complex, particularly with the emergence of AI and Big Data, the MMF concept is timely and enabling. As a new concept, it also faces various challenges. I encourage you to take the time to read the special issue and become more informed for enhancing your research productivity.