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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 : - Explain the benefits and challenges of applying NLP to extract data from clinical notes
- Better understand the role of generative AI in optimizing clinical study designs
- Evaluate the potential of ML to enable predictive treatment effect modeling from disease biology
- Contemplate the implications of generative AI from a policy perspective
Speaker(s)
Unexpected Issues in Pharmacoepidemiology Studies Applying Natural Language Processing to Clinical Notes, MOSAIC-NLP Part II
Jenna Wong, PhD, MSc
Harvard Medical School and Harvard Pilgrim Health Care Institute, United States
Assistant Professor, Department of Population Medicine
Unleashing RWD and RWE: Transforming Clinical Study Design with Generative AI
Susant Mallick, MBA
Cloudhub BV, Netherlands
Founder and CEO, Life Sciences Practice Leader
Leveraging RWD to Enable Predictive Treatment Effect Modelling in Personalized Medicine
Flavio Dormont, PhD, MBA, MS
Sanofi, United States
Therapeutic Area Head, Clinical Development RWE
Real-World Data and AI Policy
Emilie Scherrer
Tempus AI, United States
Head of HEOR
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