As the name suggests, MIE is an alternative model-based, data-analytical approach to the demonstration of BE. It integrates a number of different sources of data to model and predict BE. It involves, among other things, physiologically-based pharmacokinetic (PBPK) modeling, real-world performance data for approved generic drugs, and in silico BE assessment aimed at reducing the reliance on clinical and in vivo approaches to establishing BE. It’s a tool that FDA has been developing for its potential application to complex drugs such as long-acting depots, topically-acting inhalation and dermatological products, and other products with complex formulations – drugs with clinically challenging bioequivalence and formulation matching requirements. The pilot program will explore extending the use of MIE to less complex drugs as well.
In announcing the new pilot program, FDA acknowledged that scientific issues for non-complex products are currently not the main focus in existing FDA meetings, and as a result, it is launching a pilot program to inform the agency on how to enhance scientific communications between generic drug developers and FDA more broadly, including non-complex drugs. In a 2022 guidance, FDA described an extensive framework for meetings between ANDA sponsors and the agency for complex generics. The meetings conducted under the newly announced pilot program will focus on using a broad range of quantitative methods and modeling techniques to address generic drug development issues that are either outside the scope or cannot be sufficiently and efficiently addressed by the pre-ANDA and ANDA meetings established under the Generic Drug User Fee Amendments of 2022 (GDUFA III).
Sponsors selected for the pilot program will receive extra meetings with agency officials to examine questions including:
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if and/or how the proposed modeling approaches can be used in a specific drug development program,
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how to advance modeling methodology to address common issues of multiple products from the same applicant, and/or
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how to address complex issues as they arise and implement innovative approaches in the development of non-complex products.
The stated focus of the program will be on:
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Innovative MIE-focused approaches for BE establishment that cannot be effectively addressed under the existing GDUFA scientific meetings;
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Non-complex products with complex approaches/modeling (e.g., biopharmaceutics Classification System (BCS)-based biowaivers or other study waivers); and,
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Novel data analytics tools and approaches (e.g., machine learning and artificial intelligence) for BE establishment and assessment.
The pilot program is notably small is scale. It’s impact is unclear. The MIE approach remains largely untested. But the overall goal is geared to reducing reliance on in vivo studies in generic drug development, and to extend the use of in vitro, in silico, and biowaiver options, including the use of model-integrated approach to potentially increase the use of BCS waivers.
This wider trend is of concern to the extent it reaches beyond the science. Brand manufacturers should be on the lookout for premature changes; for example, new or revised product-specific BE guidances indicating the adoption of these alternate approaches to BE. We continue to cast a critical eye at these alternate approaches, and we intend to closely monitor the potential use of MIE for complex and non-complex generics alike, and to update our innovator clients on potential shortfalls in FDA’s methods and where we see these programs developing.
If you have questions on establishing bioequivalence for complex and non-complex drugs, on MIE, or FDA drug applications more generally, feel free to contact the Hogan Lovells attorney with whom you generally work or the author of this alert.
Authored by Jason Conaty
