GDUFA Research Outcomes
Quantitative Methods & Models
The Generic Drug User Fee Amendments (GDUFA) science and research program facilitates patient access to high-quality generic drugs by advancing research in areas where generic product development has been limited or prevented due to knowledge gaps about the kind of evidence needed to demonstrate that a generic product is the same as its brand name reference listed drug product. Leaders and experts across the generic industry collaborate to establish GDUFA research priorities for the most pressing scientific challenges they face with generic product development. Scientists and clinicians from industry, academia, and the U.S. Food and Drug Administration (FDA) strategically design research in these areas so that the outcomes help to build scientific bridges across the knowledge gaps, thereby facilitating pharmaceutical manufacturers to develop generic drugs that were previously challenging or unfeasible to develop.
A major GDUFA science and research priority is to facilitate the utility of model-integrated evidence (MIE) to support demonstrations of bioequivalence (BE). The advancement of research in this area focuses on developing tools and advancing approaches to integrate complementary in silico (modeling), in vivo, and in vitro evidence in ways that collectively mitigate the risk of failure modes for BE and support a framework for virtual BE studies. For example, while it may not be feasible to adequately characterize the long-term bioavailability of drugs from LAI products using in vivo or in vitro methods alone, it may be feasible to integrate limited in vivo and in vitro data with PBPK models that generate the remaining evidence needed to support a demonstration of BE. This area includes research on the use of MIE to evaluate failure modes for BE and to optimize the design of BE studies.
Outcomes including scientific publications, presentations, and posters arising from GDUFA-funded research in this priority area are available in this section.
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Prediction of Food Effect on In Vitro Drug Dissolution into Biorelevant Media: Contributions of Solubility Enhancement and Relatively Low Colloid Diffusivity
Polli, James E.
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Development of a CFD-PK Nasal Spray Model with In Vivo Human Subject Validation
Dutta, R; Kolanjiyil, AV; Golshahi, L; Longest, P
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Regulatory Science to Promote Access to Intrauterine Systems for Women in the United States
Sharan, Satish; Wang, Yan; Donnelly, Mark; Zou, Yuan; Fang, Lanyan; Kim, Myong Jin; Zhao, Liang
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Effect of Oral Ranitidine on Urinary Excretion of N-Nitrosodimethylamine (NDMA)
Florian, Jeffry; Matta, Murali; Depalma, Ryan; Gershuny, Victoria; Patel, Vikram; Hsiao, Cheng-Hui; Zusterzeel, Robbert; Rouse, Rodney; Prentice, Kristin; Nalepinski, Colleen Gosa; Kim, Insook; Yi, Sojeong; Zhao, Liang; Yoon, Miyoung; Selaya, Susan; Keire, David; Korvick, Joyce
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Physiologically Based Pharmacokinetic Model to Support Ophthalmic Suspension Product Development
Lemerdy, Maxime; Tan, Mingliang; Babiskin, Andrew; Zhao, Liang
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Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches: A Workshop Overview
Babiskin, Andrew; Wu, Fang; Mousa, Youssef; Tan, Ming-Liang; Tsakalozou, Eleftheria; Walenga, Ross; Yoon, Miyoung; Raney, Sam G; Polli, James E; Schwendeman, Anna; Krishnan, Vishalakshi; Fang, Lanyan; Zhao, Liang
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Validating CFD Predictions of Highly Localized Aerosol Deposition in Airway Models: In Vitro Data and Effects of Surface Properties
Longest, Worth
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Effects of Subject-Variability on Nasally Inhaled Drug Deposition, Uptake, and Clearance
Chari, Sriram; Sridhar, Karthik; Kleinstreuer, Clement
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A quasi-3D model of the whole lung: airway extension to the tracheobronchial limit using the constrained constructive optimization and alveolar modeling, using a sac���trumpet model
Kannan, Ravishekar; Singh, Narender; Przekwas, Andrzej; Zhou, Xianlian; Walenga, Ross; Babiskin, Andrew
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Validating CFD Predictions of Nasal Spray Deposition: Inclusion of Cloud Motion Effects for Two Spray Pump Designs
Kolanjiyil, Arun V; Hosseini, Sana; Alfaifi, Ali; Farkas, Dale; Walenga, Ross; Babiskin, Andrew; Hindle, Michael; Golshahi, Laleh; Longest, P Worth