FDA Regulation of Artificial Intelligence / Machine Learning

FDA Regulation of Artificial Intelligence / Machine Learning

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’s for years, however, AI/ML programs fall outside the scope of these regulations and guidance’s. This happens because FDA approves the final, validated version of the software. The point of AI/ML is to learn and update following deployment to improve performance. Thus the field version of the software is no longer the validated approved version.

We will discuss the current regulatory requirements, how they don’t control AI/ML adequately, and approaches FDA is considering for regulation in the near future. Your development program should conform to these concepts now because, with some modifications, they will probably become regulations.

Following 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.

Why You Should 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 labelling requirements
  • Cybersecurity

Who Should Attend:

  • Quality Assurance Departments
  • Research and Development Departments
  • Regulatory Affairs Departments
  • Engineering Departments
  • Software Engineers
  • Marketing Departments
  • IT Departments
  • Management Teams

FDB3397

Edwin Waldbusser

Edwin Waldbusser retired from industry after 30 years in management of development of medical device products and development of company Quality Systems. He was involved in the development of products such as IVD devices, kidney dialysis systems and inhalation devices. His QS experience includes, design control, risk analysis, CAPA, software validation, supplier qualification/ control and manufacturing/non-conforming product programs. He now consults in the area of quality systems for medical devices with emphasis on design control, software validation, risk analysis and human factors analysis. Ed has a B.S. Mechanical Engineering from NYU and a M.B.A from Drexel University. He is certified by Lloyds of London as an ISO 9000 Lead Auditor and is a member of the Thomson Reuters Expert Witness network. He has 5 issued patents.
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