June 25, 2026
Title: Beyond the Research Assistant: Innovative Uses of AI in Health Preference Research
Thursday, June 25, 2026
10:00AM EDT | 2:00PM UTC | 4:00PM CEST
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Description
Artificial intelligence (AI) is rapidly expanding the possibilities for health preference research (HPR) and related fields, moving beyond research assistance toward applications that transform how data are analyzed and interpreted. While this session is oriented to health preference research, it will be relevant to those working in patient-centered research, clinical outcomes assessment (COA), and evidence generation.
Assistive AI tools can support tasks, such as text generation, survey assistance, and qualitative coding. However, transformative applications integrate AI into the core analytical stages of preference research, using it to synthesize evidence across studies, model complex decision-making processes, and predict patient treatment preferences. This webinar will explore why these applications are becoming increasingly relevant in health preference research today.
This session will illustrate how AI-enabled approaches may reshape elements of the research lifecycle, while also highlighting validation challenges, oversight requirements, and practical constraints. Applied case examples will demonstrate how AI can support evidence synthesis and preference prediction, alongside a structured discussion of methodological implications, validation challenges, and governance considerations.
Michael Bui, MSc, will introduce the distinction between assistive and transformative AI applications, highlight why AI is becoming relevant in HPR, and discuss the types of AI tools in scope, including meta-analysis and preference prediction. Paola Berchialla, PhD, will present AI-enabled meta-analysis workflows, including automated attribute extraction, standardization across studies, and meta-analytic pooling, with methodological insights, limitations, and a live demonstration. Semra Ozdemir, PhD, will present AI-driven preference prediction, exploring how AI can anticipate patient treatment choices and its implications for research and decision-making.
By combining practical demonstrations with critical appraisal, participants will gain insight into emerging AI-enabled approaches in HPR that extend beyond currently published guidance.
Moderator:
- Jaein Seo, PharmD, MHS, Senior Research Associate, Thermo Fisher Scientific,
Wilmington, NC, USA
Speakers:
- Michael Bui, MSc, PhD candidate, Health Technology and Services Research, University of Twente, Enschede, Netherlands
- Paola Berchialla, PhD, Full Professor, University of Torino, Torino, IT
- Semra Ozdemir, PhD, Associate Professor, Duke University,
Durham, NC, USA
Presented by the ISPOR Health Preference Research Special Interest Group.