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Myths vs Reality: Generative AI and LLMs in Drug Development and Real-World Evidence Generation
Session Chair(s)
Wesley Anderson, PHD
Scientist, Quantitative Medicine
Critical Path Institute, United States
Generative AI and large language models (LLMs) are reshaping drug development and Real-World Evidence (RWE). This session explores real-world applications, debunks common myths, and outlines what’s needed for safe, scalable, and compliant use across the drug development lifecycle.
Learning Objective : Distinguish between the current capabilities and limitations of generative AI and large language models (LLMs) in RWE and drug development; Identify practical and regulatory challenges in adopting GenAI across evidence generation workflows; Explore future opportunities for integrating GenAI into the various areas of the drug development pipeline.
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