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
-
Leveraging Artificial Intelligence (AI) and Machine Learning (ML) to Support Generic Drug Development and Regulatory Efficiency
Hu, Meng
-
Leveraging Artificial Intelligence (AI) and Machine Learning (ML) to Support Regulatory Efficiency – Current Progress
Hu, Meng
-
Utility of Artificial Intelligence to Facilitate the Development and Regulatory Assessment of Complex Generic Drugs
Hu, Meng
-
Development of a Data/Text Analytics Tool to Enhance Quality and Efficiency of Bioequivalence Assessment
Hu, Meng
-
Activity Of Inactive Ingredients: Foundations For Innovation In Drug Excipients
Pottel, Josh; Algaa, Enkhjargal; Irwin, John; Shoichet, Brian
-
Machine Learning For Adverse Drug Event Detection
Page, David
-
Complex Drug Product Landscape
Jiang, Wenlei
-
Post-marketing Surveillance of Generic Drug Usage and Substitution Patterns
Jiang, Wenlei
-
Quantitative Methods for Determining Equivalence of Particle Size Distributions
Hu, Meng
-
Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis
Hu, Meng