Integrating Generative AI into the Life Sciences Industry to Move the Needle from Drug Development to Regulatory Decisions: A Realistic Prospect or a Pipe Dream?

Presentation Time: 09:45 AM - 11:15 AM

Abstract Keywords: Large Language Models (LLMs), Usability, Drug Discoveries, Repurposing, and Side-effect, Governance of Artificial Intelligence, Natural Language Processing, Interoperability and Health Information Exchange
Primary Track: Applications
Moderator: Xiaoyan Wang, PhD in Biomedical Informatics
MelaxTech

The advent of large language models (LLMs) and generative AI, such as GPT-4, has marked the beginning of an era filled with highly efficient AI-enabled solutions for life science industry. This multi-stakeholder panel will explore the current landscape of AI in life sciences from various industrial perspectives, encompassing the health system, biotechnology, and pharmaceutical industries. We will discuss how we can rapidly learn from EHR and real-world data, leveraging industry-specific clinical AI to interpret vast datasets at an unprecedented pace, thereby accelerating drug development in life sciences. Our goal is to showcase the tangible impact of AI within life sciences, review the challenges of last-mile adoption, examine the stances of regulatory agencies on the use of AI applications, filter through the noise, and start to build a consensus on defining realistic, ethical, equitable, and efficient adoption of AI in life science applications, spanning from drug development to regulatory decisions.

Speaker(s):
Ganhui Lan, PhD
Pfizer

Phil Lindemann, BS
Epic

Xiaoyan Wang, PhD in Biomedical Informatics
MelaxTech

Ying Li, Ph.D.
Regeneron Pharmaceuticals

John Cai, MD, PhD, FAMIA
Merck