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Session 8: Machine Learning and Safety Statistics
Session Chair(s)
Stella C. Grosser, PhD, MS
Division Director, Office of Biostatistics, OTS, CDER
FDA, United States
Jerald Schindler, DrPH
Chief Executive Officer
Strategic Statistics, United States
Machine learning methods have been used in a wide variety of fields. In this session, we will examine their use in the statistical detection and analysis of medical product safety signals. Examples will include natural language processing of patient narratives post-marketing and real-time monitoring of adverse events in clinical trials. Case studies will be presented with a panel discussion and lessons learned.
Learning Objective : At the conclusion of this session, participants should be able to:- Describe the current use of ML in analysis of safety data by the pharmaceutical industry and regulatory agencies
- Identify areas of potential future applications and methods development
- Recognize advantages and pitfalls of ML in identifying safety concerns with medical products
Speaker(s)
Speaker
Jae Joon Song, PhD
Food and Drug Administration, United States
Mathematical Statistician
The Emerging Landscape on the Use of Machine Learning, Artificial Intelligence, Deep Learning, and Natural Language Processing Approaches in Drug Safety
Melvin Slaighter Munsaka, PhD, MEd, MS
AbbVie, United States
Senior Director, Head Safety Statistics