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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Model-Based Tests of Bioequivalence: Impact of a Model Misspecification
Guhl, Melanie; Mercier, F; Sharan, Satish; Feng, Kairui; Sun, G; Sun, W; Grosser, S; Zhao, Liang; Fang, Lanyan; Mentre, F; Comets, E; Bertrand, J
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Age Is a Statistically Significant Predictor of the Within Subject Variability in Dabigatran Pharmacokinetics
Gonzalez-Sales, Mario; Fan, Jianghong; Fang, Lanyan; Hu, Meng; Lionberger, Robert; Zhao, Liang
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Quantitative Modeling and Simulation to Evaluate Alternative Approaches to be Used in COVID-19 Interrupted Bioequivalence Studies
Gong, Yuqing; Feng, Kairui; Lee, Jieon; Pan, Yuzhuo; Bai, Tao; Li, Bing; Kim, Carol; Yoon, Miyoung; Zhang, Peijue; Fang, Lanyan; Zhao, Liang
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Model Based Exposure-Response Analysis of Rivaroxaban to Assess the Adequacy of Current Bioequivalence Limits in Generic New Oral Anticoagulant Drugs
Gonzalez-Sales, Mario; Mario; Fang, Lanyan; Kim, Myongjin; Zhao, Liang
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Optimal Study Design To Evaluate The Clinical Response Of Extended Release Formulations Of Methylphenidate (Mph) In A Pediatric Population
Gomeni, Roberto; Bressolle-Gomeni, Francoise; Spencer, Thomas; Faraone, Stephen
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Meta-analytic Approach to Evaluate Alternative Models for Characterizing the PK Profiles of Extended Release Formulations of MPH
Gomeni, Roberto; Bressolle-Gomeni, Francoise; Spencer, Thomas; Faraone, Stephen
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Use of a clinical response index derived from a PK/PD model to estimate the optimal in vivo release rate of extended release formulations of MPH
Gomeni, Roberto; Bressolle-Gomeni, Francoise; Spencer, Thomas; Faraone, Stephen
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In Vitro Evaluation of Regional Drug Deposition in Nasal Airways of Children Using Realistic Anatomical Replicas
Esmaeili, A; Hosseini, S; Wilkins, J; Alfaifi, A; Dhapare, S; Walenga, R; Newman, B; Schuman, T; Edwards, D; Longest, W; Hindle, M; Golshahi, L
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Impact of Variability on Therapeutic Success for Drugs with Narrow Therapeutic Index
Dahmane, Elyes; Gopalakrishnan, Mathangi; Fang, Lanyan; Gobburu, Joga; Ivaturi, Vijay
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Impact of Between-subject, Within-subject and Between-occasion Variability on Therapeutic Success for Narrow Therapeutic Index Drugs: a Bioequivalence Perspective
Dahmane, Elyes; Gopalakrishnan, Mathangi; Fang, Lanyan; Gobburu, Joga; Ivaturi, Vijay