Session (CTI)

AI is rapidly transforming healthcare research. Initially applied to automate routine analytical tasks, artificial intelligence is increasingly being explored for its potential to support evidence generation and healthcare decision-making.
In HEOR, AI may support new approaches to analyzing real-world health data, examining patient experiences, and evaluating treatment outcomes. . By strengthening the analysis of large and complex datasets, has the potential to contribute to more scalable and timely evidence generation across the therapy lifecycle.
This symposium will examine how modern AI technologies are applied to generate real-world evidence (RWE) from early development through post-launch evaluation. Speakers will share practical examples of AI in economic modeling, data organization and extraction, advanced analytics, and the integration of patient-reported outcomes while preserving their nuance and integrity. The session will discuss how these approaches are being explored in practice and the methodological considerations associated with their implementation.
The session will also address key considerations for responsible implementation. Discussion will focus on where may offer meaningful analytical contributions, where expert oversight remains essential, and where methodologies continue to evolve. Emphasis will be placed on transparency, reproducibility, validation, and governance as foundations for trustworthy AI-enabled research.
The symposium will conclude with a forward-looking discussion on how emerging approaches involving large language models, agent-based AI systems, and real-world data are being explored in areas such as digital twins and synthetic data generation The discussion will consider the potential implications of these developments for evidence generation, patient-centered research, value assessment, and healthcare decision-making, including applications such as personalized outcome simulation, continuously updating economic models, synthetic comparator construction, adaptive reimbursement strategies, and AI-assisted analytical workflows that may support evolving approaches to real-world evidence studies.
Sponsored by Corporate Partner, Thermo Fisher Scientific