Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report

Abstract

Physiologically based biopharmaceutics modeling (PBBM) is used to elevate drug product quality by providing a more accurate and holistic understanding of how drugs interact with the human body. These models are based on the integration of physiological, pharmacological, and pharmaceutical data to simulate and predict drug behavior in vivo. Effective utilization of PBBM requires a consistent approach to model development, verification, validation, and application. Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM. To address this gap, industry submitted confidential PBBM case studies to be reviewed by the regulatory agencies; software companies committed to training. PBBM cases were independently and collaboratively discussed by regulators, and academic colleagues participated in some of the discussions. Successful bioequivalence "safe space" industry case examples are also presented. Overall, six regulatory agencies were involved in the case study exercises, including ANVISA, FDA, Health Canada, MHRA, PMDA, and EMA (experts from Belgium, Germany, Norway, Portugal, Spain, and Sweden), and we believe this is the first time such a collaboration has taken place. The outcomes were presented at this workshop, together with a participant survey on the utility and experience with PBBM submissions, to discuss the best scientific practices for developing, validating, and applying PBBMs. The PBBM case studies enabled industry to receive constructive feedback from global regulators and highlighted clear direction for future PBBM submissions for regulatory consideration.

Keywords: MIDD (model informed drug development); PBBM (physiologically based biopharmaceutics model(s)(ing); PBPK (physiologically based pharmacokinetics); biopredictive dissolution; clinically relevant dissolution specifications (CRDS); drug product performance; drug product quality; patient-centric drug product quality standards; safe space; virtual bioequivalence (VBE).

Figure 1

Uses of PBBM in oral formulation development. Adapted with permission from Yuvaneshwari et al. Copyright 2022 Elsevier.

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Growth in the number of publications including the term PBBM. Pubmed (https://www.ncbi.nlm.nih.gov/pmc/) was searched between 2011 and 2023 using the following 2 queries: PBBM = (“PBBM”) AND ((“biopharmaceutic”) OR (“biopharmaceutics”) OR (“biopharmaceutical”)); PBPK AND dissolution specification(s) = ((“specification”) OR (“specifications”)) AND (“PBPK”) AND (“dissolution”) NOT (“PBBM”)

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Presentations and discussion during the 2023 PBBM workshop. https://cersi.umd.edu/physiologically-based-biopharmaceutics-modeling-pbbm-best-practices-drug-productquality

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Question 1: Please indicate the institution to which you are affiliated.

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Question 3: If you did not submit any PBBM, what were the common reasons?

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Question 5: Quality questions answered by the PBBM? 2019 data from Pepin et al.

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Question 7: What were the main reasons for the PBBM rejection? 2019 data from Pepin et al. Data are expressed as a percentage of the total rejection reasons.

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Question 8: How do you rank the risk associated with the patient when using PBBM to inform internal or regulatory decision making for the following purposes?

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Question 9: What is in your opinion the likelihood of regulatory acceptance of state-of-the-art PBBM for the following purposes?.

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Question 10: Assuming full PBPK model and PBBM validated on all rich PK data during development (e.g., 1 SAD, 1 MAD, 1 food effect study, 1 ARA study, 1 fit for purpose study with 3 variants), what should the average absolute prediction error (AAPE) for PBBM validation be?