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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Establishing Quantitative Relationships Between Changes in Nasal Spray In Vitro Metrics and Drug Delivery to the Posterior Nasal Region
Kolanjiyil, AV; Walenga, Ross; Babiskin, Andrew; Golshahi, L; Hindle, Michael; Longest, Worth
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Computational Model of In Vivo Corneal Pharmacokinetics and Pharmacodynamics of Topically Administered Ophthalmic Drug Products
German, Carrie; Chen, Zhijian; Przekwas, Andrzekj; Walenga, Ross; Babiskin, Andrew; Liang, Zhao; Fan, Jianghong; Tan, Ming-Liang
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Prediction of In Vitro Drug Dissolution into Fasted-State Biorelevant Media: Contributions of Solubility Enhancement and Relatively Low Colloid Diffusivity
Polli, James E.
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Topical Nano and Microemulsions for Skin Delivery
Nastiti, Christofori; Ponto, Thellie; Abd, Eman; Grice, Jeffrey; Benson, Heather; Roberts, Michael
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An Effective PBPK Model Predicting Dissolved Drug Transfer from a Representative Nasal Cavity to the Blood Stream
Dave, Sujal; Kleinstreuer, Clement; Chari, Sriram
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Effect of Inflow Conditioning for Dry Powder Inhalers
Singh, Gajendra; Lowe, Albyn; Azeem, Athiya; Cheng, Shaokoon; Chan, Hak-Kim; Walenga, Ross; Kourmatzis, Agisilaos
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Development of a Stochastic Individual Path (SIP) Model for Predicting the Tracheobronchial Deposition of Pharmaceutical Aerosols: Effects of Transient Inhalation and Sampling the Airways
Tian, Geng; Longest, Worth; Su, Guoguang; Walenga, Ross; Hindle, Michael
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Multi-Phase Multi-Layer Mechanistic Dermal Absorption (MPML MechDermA) Model to Predict Local and Systemic Exposure of Drug Products Applied on Skin
Patel, N; Clarke, J F; Salem, F; Abdulla, T; Martins, F; Arora, S; Tsakalozou, E; Hodgkinson, A; Arjmandi-Tash, O; Cristea, S; Gosh, P; Alam, K; Raney, Sam G; Jamei, M; Polak, S
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Predicting Systemic and Pulmonary Tissue Barrier Concentration of Orally Inhaled Drug Products
Singh, Narender; Kannan, Ravi; Arey, Ryan; Walenga, Ross; Babiskin, Andrew; Przekwas, Andrzej
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Review of Complex Generic Drugs Delivered Through the Female Reproductive Tract: The Current Competitive Landscape and Emerging Role of Physiologically Based Pharmacokinetic Modeling to Support Development and Regulatory Decisions
Donnelly, Mark; Tsakalozou, Eleftheria; Sharan, Satish; Straubinger, Thomas; Bies, Robert; Zhao, Liang