# Current challenges and the way forwards for regulatory databases of artificial intelligence as a medical device

## TL;DR

This paper discusses the challenges in regulating AI as medical devices and suggests ways to improve global regulatory efforts for safer and more effective AI in healthcare.

## Contribution

The paper introduces a roadmap for improving regulatory data ecosystems for AIaMDs and emphasizes global collaboration.

## Key findings

- Four key challenges in regulatory databases for AIaMDs are identified.
- Emerging initiatives aim to address limitations in data quality and availability.
- A next-generation regulatory data ecosystem is proposed for safer AI innovation.

## Abstract

Effective regulatory oversight is a key step in ensuring that artificial intelligence as a medical device (AIaMD) is safe in real-world clinical settings. In this Perspective, we provide insights from our experience working with international regulatory databases, informed by our recent research and the expertise of the multidisciplinary authorship team. We highlight four key challenges, discuss attempts to circumvent these limitations, and highlight emerging initiatives. Nevertheless, the underlying issue of the quality and availability of input data from regulatory databases remains. We discuss considerations for improving accessibility and transparency, outline key aspects for a next-generation regulatory data ecosystem for AIaMDs, and call on global stakeholders to come together and align efforts to develop a clear roadmap to accelerate safe innovation and improve outcomes for patients worldwide.