AI-Powered Evidence Synthesis in SLRs and TLRs: Navigating Divergent HTA Guidance and Expanding Use Beyond Regulatory Submissions

Moderator

Sven Demiya, MBA, MSc, PhD, IQVIA, Minato-ku, Japan

Speakers

Yvonne Lee, MPH, PhD, IQVIA Solutions Asia, Singapore, Singapore; Keiko Asakawa, Astellas Pharma Inc, Tokyo, Japan; Ataru Igarashi, PhD, Faculty of Pharmacy, Tokyo University, Tokyo, Japan

ISSUE: Artificial intelligence (AI) is rapidly transforming evidence generation in health economics and outcomes research (HEOR), particularly in systematic and targeted literature reviews (SLRs/TLRs). Its application spans both HTA and non HTA contexts—including clinical development, market access, real world evidence (RWE), and medical affairs—enabling more efficient synthesis of large, complex evidence bases and supporting faster, more scalable, and consistent workflows.However, expectations for the use of AI in evidence synthesis remain fragmented across HTA bodies. Requirements related to transparency, reproducibility, validation, and human oversight vary considerably by jurisdiction, reflecting differing levels of maturity in the adoption and governance of AI methodologies. This inconsistency creates uncertainty for stakeholders conducting multi-country submissions and broader evidence generation programs, particularly in the absence of a harmonized framework. OVERVIEW: This panel convenes international experts to examine the current and emerging role of AI in systematic and targeted literature review (SLR/TLR) workflows across both HTA and non HTA settings. As AI adoption accelerates, stakeholders must navigate increasing evidence volume, methodological complexity, and divergent regulatory expectations. Panelist A will outline how AI is being applied across SLR/TLR workflows—including clinical evidence generation, real-world evidence (RWE), and medical affairs—and highlight where industry adoption is advancing ahead of formal methodological guidance. Panelist B will explore how HTA bodies (e.g., NICE, CADTH/CDA, PBAC, C2H) approach AI-assisted evidence synthesis, focusing on differences in expectations for transparency, reproducibility, validation, and human oversight; Panelist B will share practical strategies for aligning AI-enabled workflows. Panelist C will provide an academic perspective on how Western and Eastern HTA systems are adapting to AI use, including insights from the Japanese regulatory context and implications for cross-regional alignment. The session will conclude with an interactive discussion.

Topic

Health Policy & Regulatory, Health Technology Assessment, Methodological & Statistical Research

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