GDUFA Research Outcomes
Data Analytics and AI
This section contains scientific publications, presentations, and posters arising from GDUFA-funded research relevant to data analytics and artificial intelligence (AI) for generic product development and assessment, including the development of natural language processing (NLP) and machine learning (ML) tools
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Predicting Future Generic Drug Competition: Powering Strategic Planning Using Quantitative Methods and Modeling
Zhao, Liang
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Big Data Application in Life Sciences
Zhao, Liang
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Regulatory Science Issues in the Effect of Microbimes on Bioequivalence Determination for Generic Drug Products
Zhang, Lei
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Developing a Statistical Approach to Facilitate Sameness Assessment of Complex Heterogenous Active Pharmaceutical Ingredients
Weng, Yu Ting; Hu, Meng; Zhao, Liang; Wang, Chao; Shen, Meiyu; Gong, Xiajing
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IVPT Data Challenges and Statistical Analysis
Ghosh, Priyanka
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Alternatives to f2 Testing for Dissolution Similarity – f2 Bootstrapping and Multivariate Statistical Distance (MSD) Method
Gong, Xiajing
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An Open Access Excipients Database and Its Use to Investigate Their Possible Biological Targets
Shoichet, B
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Changing Physician and Patient Perceptions about Generic Drugs
Sarpatwari, Ameet
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Provider-Level Variation And Determinants Of Outpatient Generic Prescribing In A Mixed-Payer Healthcare System
Romanelli, Robert; Nimbal, Vani; Segal, Jodi
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Use of Data Analytics Approaches to Support Regulatory Assessment – from FDA Perspective
Hu, Meng