戻る Agenda
Session 9: Is the Future Here, Near, or Neither? Exploring the Intersection of AI and RWD in Pharmacoepidemiology
Session Chair(s)
Keri Monda, PHD, MS
Executive Director, Center for Observational Research, Amgen, United States
This session will highlight current innovative explorations when applying artificial intelligence to RWD sources. The first presentation will share lessons learned and opportunities for extracting and incorporating data from unstructured EHR clinical notes using NLP into structured data to improve the validity of pharmacoepidemiology studies. The second presentation will discuss principles and present case studies around using generative AI to transform the design of clinical studies. The third presentation delves into the details of using ML to optimize patient selection for clinical trials as viewed from a personalized medicine lens. We will wrap up with an exploration of numerous policy principles that can inform the development of effective policy and regulatory frameworks on the intersection of RWD and AI.
Learning Objective : - Demonstrate the benefits and challenges of using information extracted from clinical notes using NLP in a pharmacoepidemiology study
- Better understand the role of generative AI in optimizing clinical study designs
- Evaluate the potential of ML to enable predictive treatment effect modeling from real-world data
- Contemplate the implications of generative AI from a policy perspective
Speaker(s)
Jenna Wong, PHD, MSC
Assistant Professor, Department of Population Medicine , Harvard Medical School and Harvard Pilgrim Health Care Institute, United States
Natural Language Processing in Pharmacoepidemiology: Lessons from the Multi-source Observational Safety study for Advanced Information Classification using NLP (MOSAIC-NLP)
Susant Mallick, MBA
Founder and CEO, Life Sciences Practice Leader, Cloudhub BV, Netherlands
Unleashing RWD and RWE: Transforming Clinical Study Design with Generative AI
Flavio Dormont, PHD, MBA, MS
Therapeutic Area Head, Clinical Development RWE, Sanofi, United States
Leveraging RWD to Enable Predictive Treatment Effect Modelling in Personalized Medicine
Emilie Scherrer, MS
Head of Health Economics & Outcomes Research, Tempus AI, United States
The Role of Real-World Data in AI Policy