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FDA Regulation of Artificial Intelligence/ Machine Learning

instructor
By: Edwin Waldbusser
Schedule: 15 July, 2022 (Friday)
Time: 12:00 PM PST | 03:00 PM EST
Duration: 60 Minutes
Webinar ID : 1752

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Webinar Details

AI/ ML will revolutionize medicine by making diagnosis and treatment more accessible and more effective.
FDA has regulated medical 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 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 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.

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.

AREA COVERED

  • 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?

Managers, Supervisors, Directors, and Vice-Presidents in the areas of:

  • Software Engineers
  • Engineers
  • Regulatory Personnel
  • Quality Assurance Personnel
  • Marketing
  • Management

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.

  • 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

Managers, Supervisors, Directors, and Vice-Presidents in the areas of:

  • Software Engineers
  • Engineers
  • Regulatory Personnel
  • Quality Assurance Personnel
  • Marketing
  • Management

SPEAKER PROFILE

instructor

Edwin Waldbusser, is a consultant retired from industry after 20 years in management of development of medical devices (5 patents). He has been consulting in the areas of design control, risk analysis and software validation for the past 8 years. Mr. Waldbusser has a BS in Mechanical Engineering and an MBA. He is a Lloyds of London certified ISO 9000 Lead Auditor and a member of the Thomson Reuters Expert Witness network.

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