Scaling medical device regulatory science using large language models.

Abstract

Advances in artificial intelligence (AI) and machine learning (ML) have led to a surge in AI/ML-enabled medical devices, posing new challenges for regulators because best practices for developing, testing, and monitoring these devices are still emerging. Consequently, there is a critical need for up-to-date data analyses of the regulatory landscape to inform policy-making. However, such analyses have historically relied upon manual annotation efforts because regulatory documents are unstructured