Public Workshop Summary Report on Fiscal Year 2021 Generic Drug Regulatory Science Initiatives: Data Analysis and Model‐Based Bioequivalence

Abstract

On May 4, 2020, the US Food and Drug Administration (FDA) hosted an online public workshop titled "FY 2020 Generic Drug Regulatory Science Initiatives Public Workshop" to provide an overview of the status of the science and research priorities and to solicit input on the development of Generic Drug User Fee Amendments fiscal year 2021 priorities. This report summarizes the podium presentations and the outcome of discussions along with innovative ways to overcome challenges and significant opportunities related to model-based approaches in bioequivalence assessment for breakout session 4 titled, "Data analysis and model-based bioequivalence (BE)." This session focused on the application of model-based approaches in the generic drug development, with a vision of accelerating regulatory decision making for abbreviated new drug application assessments. The session included both podium presentations and panel discussions with three topics of interest: (i) in vitro study evaluation methods and their clinical relevance, (ii) challenges in model-based BE, (iii) emerging expertise and tools in implementing new BE approaches.

Model‐Informed Drug Development: Connecting the Dots With a Totality of Evidence Mindset to Advance Therapeutics

“…Model‐informed approaches are enabling abbreviated new drug applications for generic drugs to substantiate evidence through model‐based bioequivalence, as reviewed by Lee et al . in their summary of a session on the topic in a Generic Drug Regulatory Science Initiatives Public Workshop held in May 2020 26 . In their recently published White Paper, Fang et al .…”

“…Model-informed approaches are enabling abbreviated new drug applications for generic drugs to substantiate evidence through modelbased bioequivalence, as reviewed by Lee et al in their summary of a session on the topic in a Generic Drug Regulatory Science Initiatives Public Workshop held in May 2020. 26 In their recently published White Paper, Fang et al reviewed considerations for demonstrating bioequivalence among products for which a rapid onset of pharmacologic effect or a controlled duration of effect are of therapeutic importance, using the alternate metric of partial area under the curve (AUC). 27 They provided a valuable overview of the regulatory history of development of the approach with illustrative examples of how product-specific partial AUC end points have been rationalized.…”

Predictive Dissolution Models for Real-Time Release Testing: Development and Implementation - Workshop Summary Report

“…9). The successful implementation of a FPDM will then facilitate the selection of the true CMAs and CPPs (41,42). To this end, FPDM testing then serves as both a sensor of potential interactions among parameters and an indicator representing the impact of implemented CMC changes on in vivo performance.…”

Physiologically‐Based Pharmacokinetic Modeling to Support Determination of Bioequivalence for Dermatological Drug Products: Scientific and Regulatory Considerations

“…Physiologically‐based pharmacokinetic (PBPK) modeling and simulation is a quantitative methodology that mechanistically describes the disposition (i.e., absorption, distribution, metabolism, and elimination) of an active ingredient in the human body. Although the concept of PBPK modeling was introduced over 70 years ago, 1,2 the role of sophisticated PBPK models that integrate information on the human physiology, the properties of the active ingredient, and the drug product quality attributes has been recently established 3–8 . In the new drug development space, PBPK models are utilized to inform dose selection (first‐in‐human studies) and dose optimization, interspecies extrapolations, dose adjustments in specific populations (pregnancy, pediatrics, and organ impairment), and evaluation of potential drug‐drug interactions 3,6,7,9,10 .…”

“…In the new drug development space, PBPK models are utilized to inform dose selection (first‐in‐human studies) and dose optimization, interspecies extrapolations, dose adjustments in specific populations (pregnancy, pediatrics, and organ impairment), and evaluation of potential drug‐drug interactions 3,6,7,9,10 . Mechanistic PBPK models for generics guide the establishment of clinically relevant product quality attributes and provide a risk‐based assessment when formulation changes are introduced 8,11–14 . When PBPK models account for population variability, they may provide reliable population simulations leveraged toward virtual bioequivalence (VBE) assessments 15–20 …”