FDA regulation of Artificial Intelligence/ Machine Learning programs

Overview:
AI/ ML will revolutionize medicine by making diagnosis and treatment more accessible and more effective. FDA has regulated medical software by means of regulation and guidance for years, however, AI/ML programs fall outside the scope of these regulations and guidance. This happens because the FDA approves the final, validated version of the software. The point of AI/ML is to learn and update the following deployment to improve performance. Thus the field version of the software is no longer the validated approved version.

This training will address the current regulatory requirements, how they don’t control AI/ML adequately, and approaches FDA is considering for regulation in the near future. Development personnel should understand these concepts because, with some modifications, they will probably become regulations.
It is not clear how to get AI/ML programs approved. Following the discussion of possible future regulation, we will discuss, based on recently approved De Novo applications, how to get your AI/ML program approved now.

Necessary submission documentation will be explained.

This webinar is not a programming course but will explain the present and future regulatory requirements for AI/ML. Attendees will receive a multipage outline and checklist.

Why Should You Attend:
It is not clear how to get AI/ML programs approved. The current regulatory requirements don’t control AI/ML adequately.

We will discuss the approaches FDA is considering for regulation in the near future and how to get your AI/ML program approved by the FDA now. Necessary submission documentation will be explained.

Attendees will receive a multipage outline and checklist.

Areas Covered in the Session:
•  Total product life cycle approach to AI/ ML design
•  Application of FDA software Pre Cert program to AI/ ML
•  FDA discussion paper on AI/ML
•  Database management
•  QC of datasets
•  Algorithm updating
•  Reference standard development
•  Standalone performance testing
•  Clinical performance testing
•  Data enrichment
•  Emphasis on “explainability”
•  Additional labeling requirements
•  Cybersecurity

Who will benefit:
•  Software Engineers
•  Engineers
•  Regulatory personnel
•  Quality Assurance personnel
•  Marketing
•  Management