How government agencies use HealthVerity for public health and AI-powered research
The FDA needed to speed up its drug approval process while keeping safety and efficacy standards intact, requiring trustworthy AI frameworks for analyzing large healthcare datasets. In January 2025 the FDA issued draft guidance setting out a risk-based framework for sponsors to assess AI model credibility in regulatory submissions, and HealthVerity Marketplace — described as offering "75+ distinct data sources and 340+ million de-identified patients in a single, unified environment" with transparent, auditable dataset provenance — supports that framework by supplying real-world data. The stated goal is to help the FDA "get quicker insights from data so they can get drug products out faster."
HealthVerity is a real-world-data marketplace aggregating claims, EHR and lab data from 75+ sources via a proprietary patient-matching layer.
This sits in the Data Providers stage of the AI use-case lifecycle: Named examples from the real-world-data, claims and competitive-intelligence providers pharma AI systems are trained on, benchmarked against, or run inside of.
Published by HealthVerity on its own site — read the original case study on blog.healthverity.com ↗
Note: Source page covers ARPA-H, FDA, and NIH together in one article; this entry reflects only the FDA section.
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