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Bois FY, Brochot C. A Bayesian framework for virtual comparative trials and bioequivalence assessments. Front Pharmacol 2024; 15:1404619. [PMID: 39139647 PMCID: PMC11319711 DOI: 10.3389/fphar.2024.1404619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 07/02/2024] [Indexed: 08/15/2024] Open
Abstract
Introduction In virtual bioequivalence (VBE) assessments, pharmacokinetic models informed with in vitro data and verified with small clinical trials' data are used to simulate otherwise unfeasibly large trials. Simulated VBE trials are assessed in a frequentist framework as if they were real despite the unlimited number of virtual subjects they can use. This may adequately control consumer risk but imposes unnecessary risks on producers. We propose a fully Bayesian model-integrated VBE assessment framework that circumvents these limitations. Methods We illustrate our approach with a case study on a hypothetical paliperidone palmitate (PP) generic long-acting injectable suspension formulation using a validated population pharmacokinetic model published for the reference formulation. BE testing, study power, type I and type II error analyses or their Bayesian equivalents, and safe-space analyses are demonstrated. Results The fully Bayesian workflow is more precise than the frequentist workflow. Decisions about bioequivalence and safe space analyses in the two workflows can differ markedly because the Bayesian analyses are more accurate. Discussion A Bayesian framework can adequately control consumer risk and minimize producer risk . It rewards data gathering and model integration to make the best use of prior information. The frequentist approach is less precise but faster to compute, and it can still be used as a first step to narrow down the parameter space to explore in safe-space analyses.
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Affiliation(s)
- Frederic Y. Bois
- Certara UK Limited, Certara Predictive Technologies Division, Sheffield, United Kingdom
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Tsakalozou E, Gong Y, Babiskin A, Hu M, Mousa Y, Walenga R, Wu F, Yoon M, Raney SG, Polli JE, Schwendeman A, Krishnan V, Fang L, Zhao L. Application of Advanced Modeling Approaches Supporting Generic Product Development Under GDUFA for Fiscal Year 2023. AAPS J 2024; 26:55. [PMID: 38658449 DOI: 10.1208/s12248-024-00924-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 04/11/2024] [Indexed: 04/26/2024] Open
Affiliation(s)
- Eleftheria Tsakalozou
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA.
| | - Yuqing Gong
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Andrew Babiskin
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Meng Hu
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Youssef Mousa
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Ross Walenga
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Fang Wu
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Miyoung Yoon
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Sam G Raney
- Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - James E Polli
- Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland, USA
| | - Anna Schwendeman
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Vishalakshi Krishnan
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Lanyan Fang
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Liang Zhao
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
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Tsakalozou E, Fang L, Bi Y, van den Heuvel M, Ahmed T, Tsang YC, Lionberger R, Rostami-Hodjegan A, Zhao L. Experience Learned and Perspectives on Using Model-Integrated Evidence in the Regulatory Context for Generic Drug Products-a Meeting Report. AAPS J 2024; 26:14. [PMID: 38200397 DOI: 10.1208/s12248-023-00884-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/14/2023] [Indexed: 01/12/2024] Open
Abstract
This report summarizes relevant insights and discussions from a 2022 FDA public workshop titled Best Practices for Utilizing Modeling Approaches to Support Generic Product Development which illustrated how model-integrated evidence has been used and can be leveraged further to inform generic drug product development and regulatory decisions during the assessment of generic drug applications submitted to the FDA. The workshop attendees discussed that model-integrated evidence (MIE) approaches for generics are being applied in the space of long-acting injectable (LAI) products to develop shorter and more cost-effective alternative study designs for LAI products. Modeling and simulation approaches are utilized to support virtual BE assessments at the site of action for locally acting drug products and to assess the impact of food on BE assessments for oral dosage forms. The factors contributing to the success of the model-informed drug development program under PDUFA VI were discussed. The generic drug industry shared that decisions on formulation candidate/formulation variant selection, on pilot in vivo bioavailability studies, and on alternative study designs for BE assessment are informed by modeling and simulation approaches. There was agreement that interactions between the regulatory agencies and the industry are desirable because they improve the industry's understanding of scientific and other regulatory considerations on implementing modeling and simulation approaches in drug development and regulatory submissions.
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Affiliation(s)
- Eleftheria Tsakalozou
- Division of Quantitative Methods and Modeling, Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration (FDA), 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA.
| | - Lanyan Fang
- Division of Quantitative Methods and Modeling, Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration (FDA), 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
| | - Youwei Bi
- Office of Clinical Pharmacology, Office of Translational Sciences, CDER, FDA, Silver Spring, Maryland, USA
| | | | - Tausif Ahmed
- Biopharmaceutics and Bioequivalence Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad, 500 090, Telangana, India
| | | | - Robert Lionberger
- Office of Research and Standards (ORS), Office of Generic Drugs (OGD), CDER, FDA, Silver Spring, Maryland, USA
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
- Certara Inc., Princeton, New Jersey, USA
| | - Liang Zhao
- Division of Quantitative Methods and Modeling, Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration (FDA), 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA
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Walenga RL, Babiskin AH, Bhoopathy S, Clarke JF, De Backer J, Ducharme M, Kelly M, Le Merdy M, Yoon M, Roy P. Use of the Same Model or Modeling Strategy Across Multiple Submissions: Focus on Complex Drug Products. AAPS J 2024; 26:12. [PMID: 38177638 DOI: 10.1208/s12248-023-00879-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 12/04/2023] [Indexed: 01/06/2024] Open
Abstract
Evidence shows that there is an increasing use of modeling and simulation to support product development and approval for complex generic drug products in the USA, which includes the use of mechanistic modeling and model-integrated evidence (MIE). The potential for model reuse was the subject of a workshop session summarized in this review, where the session included presentations and a panel discussion from members of the U.S. Food and Drug Administration (FDA), academia, and the generic drug product industry. Concepts such as platform performance assessment and MIE standardization were introduced to provide potential frameworks for model reuse related to mechanistic models and MIE, respectively. The capability of models to capture formulation and product differences was explored, and challenges with model validation were addressed for drug product classes including topical, orally inhaled, ophthalmic, and long-acting injectable drug products. An emphasis was placed on the need for communication between FDA and the generic drug industry to continue to foster maturation of modeling and simulation that may support complex generic drug product development and approval, via meetings and published guidance from FDA. The workshop session provided a snapshot of the current state of modeling and simulation for complex generic drug products and offered opportunities to explore the use of such models across multiple drug products.
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Affiliation(s)
- Ross L Walenga
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
| | - Andrew H Babiskin
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | - Sid Bhoopathy
- Pharmaron US Lab Services and CGT, Exton, Pennsylvania, USA
| | | | | | - Murray Ducharme
- Learn and Confirm Inc., St-Laurent, Québec, Canada
- University of Montréal, Montréal, Québec, Canada
| | | | | | - Miyoung Yoon
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | - Partha Roy
- Office of Bioequivalence, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
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