FDA clears the final validated version of software and requires a new 510(k) submission if “substantial changes” are made post release. We will explain how to evaluate changes to software and hardware.
The requirement for a new 510(k) submission for a substantial change lead into the regulatory difficulty Machine Learning products find themselves.
ML product is designed to learn and update post approval and release. The
updated ML algorithm is no longer the approved validated product. Thus the
changes probably necessitate a new 510(k) submission for each update.
FDA recognizes this problem and has proposed methodology to satisfy the regulations. We will discuss this proposed FDA solution which will become a Guidance this year.
In the meantime , FDA has approved “locked” ML products. We will discuss what that is and, based on a review of the submissions of cleared ML products, what the FDA wants to see in a ML 510(k) submission so that you can get your ML product cleared now.
In this webinar we will explain what a 510(k) is and explain the other FDA regulatory pathways. We will discuss how software can be considered a device by the FDA.
The procedure to obtain a 510(k) will be explained. The contents of the submission to the FDA will be explained.
The very confusing concepts of “predicate device’ and “substantial equivalence” will be explained.
How to find an acceptable predicate device will be explained.
Note: This webinar is not a programming course but is an explanation of the regulatory process.
Areas Covered in the session:
- 510(k) regulation
- Machine Learning overview
- Machine learning conflict with the regulations
- FDA proposed solution
- Content of a ML 510(k) submission
Learning Objectives :
- Understand what a 510(k) is and the submission process to the FDA.
- Understand the regulatory issue preventing ML products from learning post 510(k) clearance. Understand the FDA’s proposed solution.
- Understand the contents of a ML 510(k) submission based on the examination of many cleared ML 510(k)’s
Why Should You Attend?
The medical device market is the largest market of all of the life sciences and it is generally valued at upwards of $90 billion with the expectation of continuous growth. This growth demands that the market be continually fed with new and innovative products.
Regulations have made the approval of products for market a complex process requiring manufacturers, to ensure their own survival, to be fully knowledgeable of the regulatory submissions process.
Understanding how to properly craft a submissions can save tremendous amounts of time and preparation cost and assure a favorable outcome.
Who will benefit?
Attendees are expected to have a basic knowledge of FDA regulations and machine learning concepts.
- Software programmers
- Quality Assurance
- Engineering personnel
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 US and internationally in the areas of design control, risk analysis and software validation for the past 11 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.
Tags: 510(k), Machine, Learning, Edwin, Waldbusser, February 2023, Webinar