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.
Every product code FDA has created for AI and ML medical devices — what each covers, when it was established, and how many devices have cleared under it.
Real clearance timeline data for AI medical devices — median review times by product code and indication, based on 950+ cleared devices.
De Novo decisions create new product codes and establish special controls — and they can be powerful predicates for 510(k) submissions.
A complete overview of FDA's current regulatory framework for AI devices — final guidance, draft guidance, enforcement trends, and what to watch for.
When your AI algorithm changes post-clearance, should you file a PCCP, a Special 510(k), or a Traditional supplement? A practical decision framework.
Every 510(k) clearance is a public document. Here's how to systematically extract competitive intelligence from FDA's public records.
An analysis of FDA warning letters involving AI diagnostic devices — what violations FDA is acting on and what to avoid.
An analysis of MAUDE reports for cleared AI devices — what types of events are being reported and what it means for regulatory strategy.
Choosing between De Novo and 510(k) is one of the most consequential regulatory strategy decisions you'll make. Here's a practical framework.
An analysis of how leading AI radiology companies used predicate strategy and PCCP to build compounding regulatory competitive advantages.
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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