July 16, 2026
Title: Harnessing AI to Transform HEOR and Real‑World Evidence Generation in Rare Diseases: Regulatory Expectations, Opportunities, and Practical Use Cases
Thursday, July 16, 2026
11:00AM EDT | 3:00PM UTC | 5:00PM CEST
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Registration Coming Soon!
Description
Rare diseases present unique challenges for health economics and outcomes research (HEOR) and real‑world evidence (RWE) generation, including small patient populations, fragmented data, and high evidentiary uncertainty for regulators and payers. Artificial intelligence (AI) offers opportunities to address these barriers by enabling more efficient data integration, advanced analytics, and innovative evidence generation approaches.
This webinar will examine the application of AI driven methods such as feature engineering, causal machine learning, natural language processing, and hybrid modeling approaches across HEOR and RWE workstreams in rare disease. Topics will include patient identification/phenotyping across structured and unstructured data, natural history and disease progression modeling, synthetic data generation, digital twins, external control arms, treatment effect estimation, and evidence synthesis to support value demonstration and access negotiations.
We will also explore evolving regulatory and health technology assessment (HTA) perspectives on AI enabled RWE, including expectations for algorithm development and validation, data provenance and quality, model interpretability, bias assessment, and reproducibility. Emphasis will be placed on aligning AI enabled analyses with regulatory frameworks for fit for purpose evidence in submissions to agencies and HTA bodies.
Real world use cases will illustrate how AI can enhance analytical rigor and efficiency while meeting evidentiary standards for rare disease decision making and patient access.
Learning Objectives
- Emerging regulatory and HTA expectations for AI based HEOR and RWE analyses.
- Practical applications of AI across HEOR and RWE workstreams for rare diseases.
- Considerations for ensuring transparency, reproducibility, and trustworthiness in AI‑generated insights.
- Strategic considerations for organizations seeking to responsibly integrate AI into evidence and access functions.
Moderator:
Jackie Vanderpuye-Orgle, SVP, Advanced Analytics, Access Consulting, Parexel
Speakers:
Tala Fakhouri, VP, AI & Digital Policy, Real-World Research, Regulatory Consulting, Parexel
Ipek Ozer Stillman, VP, Global Head of Health Economics, Takeda
Alexandra Pasi, CEO, Lucidity Sciences
Sponsored by Corporate Partner, Parexel.
Please note: On the day of the scheduled webinar, the first 1000 registered participants will be accepted into the webinar. For those who are unable to attend, or would like to review the webinar at a later date, the full-length webinar recording will be made available at the ISPOR Educational Webinar Series webpage approximately 2 days after the scheduled Webinar. Reservations are on a first-come, first-served basis.