Regulatory Intelligence
Technical, authoritative breakdowns of how FDA regulates AI-enabled medical devices — written for the people who have to get cleared.
A working method for tracing the predicate chain behind any cleared AI device — what the 510(k) summary actually tells you, where the database falls short, and how to reconstruct lineage that FDA never publishes directly.
What's actually in FDA's AI/ML-enabled device list, why the static spreadsheet falls short, and how to read it like a database.
FDA's mechanism for approving algorithm changes without a new submission — what qualifies, what doesn't, and the patterns in approved plans.
Every De Novo grant that created a new AI product code, and what its special controls mean for the devices clearing into it.
The action plans, draft guidances, and discussion papers shaping AI regulation — and what each one changes in practice.
What the warning letters reveal about FDA's posture on AI diagnostics, and where the agency is drawing its lines.
How Software as a Medical Device moves through FDA, from classification to clearance, with the decisions that matter most.
Every post is grounded in the same dataset that powers the platform.
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