Development and validation of a best practices framework for PBPK analysis for biopharmaceutic applications in support of model-informed biowaivers of fed state BE studies for BCS class II drugs

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PROJECT SUMMARY Lower-cost generic drugs generated $313 billion in savings to the US healthcare system in 2019 and approximately $2.2 trillion in the past decade. Therefore, generic drugs play a pivotal role in the sustainability of the US health system. A generic drug is approved on the basis of sufficient demonstration of sameness to the corresponding brand-name drug. Critical evidence for approval is bioequivalence (BE). Even though well established, pharmacokinetic-based BE studies are both costly and lengthy. In the case of orally administered drug products, co-administration with food may influence oral absorption, thus BE should be demonstrated under both fasting and fed conditions if the reference listed drug labeling states the product can be taken with or without meals. This requirement poses an additional financial burden on generic manufacturers, which will ultimately be passed along to patients. Furthermore, the regulatory requirement of two in vivo BE studies slows down the generic drug product development process and may increase review cycles and attrition rates due to variability that is related to the drug itself rather than the formulation. Quantitative methods and modeling have been widely used in the realm of new drug discovery and development to inform more efficient and cost-effective development programs. Physiologically-based pharmacokinetic (PBPK) modeling is one of the key tools under the overarching umbrella of quantitative models. PBPK models are an effective tool to integrate information about the product characteristics, the physiology of the individual subject, and the variability among subjects within a population to simulate the absorption and subsequent systemic disposition of the drug without conducting in vivo PK studies. PBPK models have shown promise in supporting generic drug development and regulatory decision-making, since, under a model-integrated evidence perspective, it enables the leveraging of all prior knowledge generated to support the regulatory approval of the respective brand-name drug product. We will develop a best practices framework for integrating drug and drug product data together with gastrointestinal physiology in PBPK models tailored to oral drug administration to predict food-formulation interactions and promote biowaivers of fed state BE studies for poorly soluble and highly permeable drugs. This will be done at both the individual and population levels. We have excellent in vitro testing and PBPK modeling capabilities, along with unique PK and luminal drug concentration data sets. Once established, this framework can also be applied to address emerging issues in generic drug development and assessment, such as BE study protocol changes necessitated, for example, by pandemic situations and hypochlorhydria-formulation interactions.