Embracing the AI Revolution: Exploring the Promising Future of Generative AI in HEOR

Speaker(s)

Moderator: Bill Malcolm, MSc, Bristol Myers Squibb, Middlesex, LON, UK
Panelists: Tim Reason, MSc, Estima Scientific Ltd, South Ruislip, LON, UK; Julia Langham, MSc, PhD, London School of Hygiene & Tropical Medicine, London, LON, UK; Sven L Klijn, MSc, HEOR, Bristol-Myers Squibb, Rotterdam, ZH, Netherlands

ISSUE: Should we accelerate the use of generative AI in all domains of HEOR?

OVERVIEW: The panel will delve into the ongoing advancements in generative AI and LLMs within HEOR, highlighting potential benefits, envisioning future trajectory and discussing concrete examples of generative AI producing robust outputs in evidence synthesis and economic modelling.

Tim Reason will introduce the audience to the dynamic field of generative AI, particularly focusing on Large Language Models (LLMs) and their transformative potential in healthcare. He will provide a comprehensive overview of AI and LLMs, defining key terminology, providing historical context, and emphasising how these technologies can enhance patient care, optimise resource allocation, and foster innovation in healthcare.

Julia Langham will discuss the current state of generative AI in HEOR, highlighting suitability of LLMs for HEOR-related tasks compared to previous AI approaches. She will showcase concrete examples of how LLMs can generate valuable and accurate outputs in systematic literature reviews (SLR), network meta-analyses (NMA), and economic modelling, underscoring their practical utility in HEOR research.

Sven Klijn will present a broader industry perspective on AI and LLMs, exploring key areas such as the potential implications of substantially reduced costs in generating robust scientific materials and insights within the HEOR industry. Additionally, he will discuss the broader concept of technological disruption, drawing insights from "the innovator's dilemma".

Each speaker will present their perspective in a scientifically-grounded manner within a 10-minute timeframe, followed by a 30-minute audience discussion and debate. Attendees, including stakeholders in healthcare, AI researchers, health economists, and policymakers, will gain valuable insights.

NOTE: There will be a discussion group on this topic following the session. Join us in the Discussion Lounge in Hall E North from 11:45-12:45 in Discussion Group A.

Code

102

Topic

Study Approaches