FDA Regulation of Artificial Intelligence/ Machine Learning
Instructor: Recorded: Access recorded version, only for one participant unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
Corporate Recorded: Access recorded version, Any number of participants unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
AI/ ML will revolutionize medicine by making diagnosis and treatment more accessible and more effective. FDA has regulated medical device software by means of regulations and guidance for years, however, AI/ML programs fall outside the scope of these regulations and guidances.
This happens because FDA approves the final, validated version of the software. The point of AI/ML is to learn and update the following deployment using real-world data 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 become regulations.
It is not clear how to get AI/ML programs approved. Following a discussion of possible future regulations, 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 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
- Software Engineers
- Engineers
- Regulatory personnel
- Quality Assurance personnel
- Marketing
- Management