Session (CTI)

Purpose Generative AI (GenAI) is increasingly being adopted for systematic literature reviews, yet its broader potential to accelerate additional components of the HEOR workflow—such as health economic model development and verification, and HTA submissions—remains under-recognized. The objective of this session is to present real-world applications that provide concrete evidence of GenAI’s ability to enhance efficiency, improve productivity, and maintain methodological rigor across diverse HEOR activities. Description This session will feature practitioner-led case studies illustrating how GenAI is being successfully deployed to gain productivity. The session will be moderated by Uwe Siebert, who will introduce recent advances in GenAI technologies and discuss their emerging role in reshaping HEOR workflows, quality standards, and evidence generation practices. Jag Chhatwal will present a case study on the use of GenAI to automate components of health economic model verification, including a project conducted in collaboration with NICE. He will describe how GenAI-enabled workflows applied standard verification checklists with significant efficiency gains while preserving transparency and methodological rigor. Ipek Stillman will share insights from a GenAI-supported health economic model replication project performed in industry. This presentation will highlight both the benefits and the challenges encountered when using GenAI into complex modeling tasks. Turgay Ayer will demonstrate how 1000+ agentic GenAI systems were used to generate comprehensive landscape assessment reports within 48 hours. Their case study will illustrate how multi-agent architectures can coordinate evidence gathering, synthesis, and narrative development across large information spaces to inform HEOR work. The session will conclude with a moderated discussion on best practices, limitations, risks, and key considerations for responsibly and effectively incorporating GenAI into HEOR workflows, along with implications for long-term productivity, methodological standards, and expectations of regulatory and HTA bodies.