What is AILC? The FDA’s current guidance on AI in medical devices and healthcare

Many businesses are able to simply integrate off-the-shelf AI software tools into their business practices to enhance efficiency and lessen employee workload. Medical device, pharmaceutical, and healthcare businesses are unable to do so. In these industries, the business is accountable for the safety and security of all third party tools- especially when they are integrated into medical devices, software as a medical device, or other healthcare processes or services.?

It is not surprising, then, that the biggest consulting need in AI-integration into medical devices is regulatory consulting. While pharmaceutical companies are trending towards the use of AI in drug compound identification, medical device companies (especially those developing software as a medical device) have to be extremely cautious in integrating AI into their products.?

Many regulatory professionals find advising on AI issues challenging. AI is complex, and can feel like an overwhelming new technology. Thankfully, there are a few key ways to conceptualize AI-enabled health care and devices into regulatory frameworks that regulatory professionals use every day.?

Last week, the FDA published a blog entitled “Lifecycle management approach toward delivering safe, effective, AI-enabled health care.” In this blog, we are introduced to the acronym AILC, which stands for AI lifecycle.

AILC is a way to map the traditional Software Development Lifecycle onto today’s AI technology, with the goal to provide the same process framework for all lifecycle phases of AI-enabled health care and medical devices. By following this framework, regulatory professionals can ensure they are ensuring their team maintains best practices during planning, designing, implementing, testing, integrating, deploying, maintaining, and retiring AI-enabled software. The FDA provides a helpful graphic showing these steps, and the regulatory activities that must be conducted at each phase of the AILC.

However, there is more work to be done in clarifying the role of AI and the regulatory requirements for AI-enabled health care and medical devices. The FDA ends their blog post with a call to action in four key areas. These include the need for a foundation of ethically sound data, a comprehensive checklist to aid developers, a focus on the post-deployment phase, and the development of a more harmonized approach to AI-development.

Does your company still need guidance on ow to manage the uncertain regulatory environment surrounding AI in medical devices and health care? Reach out to us on LinkedIn or at welsfordconsultingllc.com . We are happy to help with any project- big or small.