At ISPOR 2025 in Montreal, our team at Value Analytics Labs—in collaboration with Takeda Pharmaceuticals—presented groundbreaking research on the use of generative AI in health economics. Our study explored a frontier application: using large language models to replicate published cost-effectiveness models.
Value Analytics Labs made a remarkable impact at ISPOR Europe 2024, the premier event in Health Economics and Outcomes Research (HEOR). Our team showcased a series of groundbreaking presentations, highlighting our expertise and innovative approaches in leveraging Generative AI to advance HEOR methodologies.
In the first part of this series, we explored the transformative power of generative AI in Health Economics and Outcomes Research (HEOR) and Market Access (MA), highlighting practical applications and demonstrations from our recent workshop at Harvard. Now, let's dive deeper into the advanced AI skills discussed, the challenges identified, and the key takeaways that point toward the future of AI in our field.
Join Value Analytics Labs at ISPOR US from May 5-8, 2024. At ISPOR 2024, attendees will delve into the latest methodologies, data analytics, and evidence-based approaches that drive transformative changes in health and well-being. This year’s meeting is themed HEOR: A Transformative Force for Whole Health
What is clear is that more variants will emerge if people remain susceptible to catching COVID-19 in the first place, said Jagpreet Chhatwal, an assistant professor at Harvard Medical School.
In this joint interview feature, following their workshop delivered at the International Society for Pharmacoeconomics and Outcomes Research’s 2020 Asia Pacific meeting (Virtual ISPOR Asia Pacific 2020; 14–16 September), Turgay Ayer (Georgia Tech, GA, USA), Jag Chhatwal (Massachusetts General Hospital, MA, USA) and Selin Merdan (Value Analytics Lab, GA, USA) discuss the practicalities of applying machine learning (ML) in the real-world evidence and health economics and outcomes research (HEOR) fields.
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