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Bradley Merrill Thompson, RAC
Expert in Food & Drug Law and Artificial Intelligence Applications in Healthcare
Bradley Merrill Thompson, RAC, is a prominent attorney and managing member at BT Angel Investments LLC, based in Washington, D.C. He specializes in regulatory affairs within the healthcare sector, particularly focusing on food and drug law, medical devices, and digital health technologies. His extensive experience spans over 25 years in the healthcare industry, where he has played a significant role in advising companies on FDA regulatory matters, reimbursement strategies, and clinical trials.2
Professional Background
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Current Roles:
- Managing Member at BT Angel Investments LLC.
- Member at Epstein Becker & Green, P.C. since 2006, where he leads practices related to medical devices and artificial intelligence.12
- Chairman of the Board and Chief Data Scientist at EBG Advisors, Inc., overseeing multidisciplinary teams that assist healthcare companies in navigating regulatory challenges.2
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Previous Experience:
Education
Bradley holds multiple degrees:
- Juris Doctor (J.D.), Cum Laude from the University of Michigan Law School.
- Master of Business Administration (M.B.A.) in International Business from the University of Illinois.
- Master of Applied Data Science (M.A.D.S.) from the University of Michigan, where he studied algorithms and machine learning.12
Recognition
He has been recognized as a leading lawyer in his field by Chambers USA and The Best Lawyers in America, particularly noted for his expertise in FDA law and healthcare regulations.2
Bradley's analytical skills and passion for mathematics have also led him to develop initiatives that integrate artificial intelligence into healthcare solutions, reflecting his commitment to advancing the industry through innovative approaches.2
Highlights
I may be jumping the gun here, but I’m anxious to understand how the new flurry of FDA-regulated, AI medical devices is performing in the marketplace, or more specifically, whether the devices are failing to perform in a way that jeopardizes health. So this month I took a deep dive into MDRs filed for AI-driven medical devices. On the whole, I was encouraged, but there are some trends worth following.
When I was working on my Masters in data science, one of the projects I did was to create an algorithm that would take an intended use statement for a medical device and predict whether FDA would require a clinical trial. It worked fairly well, with accuracy of about 95%.
Since that’s a dynamic algorithm in which the user inputs an intended use statement and gets a prediction of FDA’s decision, I wanted to go about a similar task this month: create a static word cloud to show what words are most associated with intended use statements where FDA has required a clinical trial. At least in theory, this static representation might give you a sense of words in an intended use statement that are more likely to push your device toward a clinical trial.
