Regulatory strategy work is some of the most valuable and most time-consuming work in medtech. A single 510(k) predicate analysis can mean days of combing through FDA databases, cross-referencing product codes, reading 510(k) summaries line by line, and manually building comparison tables before a regulatory team can even start drafting Pre-Submission questions.
At NyquistAI, we've spent years structuring the FDA's sprawling, messy public data into clean, queryable intelligence. Now, with our Model Context Protocol (MCP) server, that intelligence is available directly inside AI tools like Claude. And with the arrival of Claude Skills, we can go a step further: turning our structured data into a fully automated regulatory workflow.
What Makes This Possible: NyquistAI's MCP + Claude Skills
MCP gives Claude live, structured access to NyquistAI's FDA datasets: global clinical trial registries, device clearances, guidance documents, inspection citations, adverse event reports, recalls, and registration data. Claude Skills gives Claude a repeatable, expert-defined process for using that data toward a specific outcome.
Put them together, and you get something new: an AI agent that doesn't just answer questions about FDA data, but actually executes the kind of multi-step regulatory analysis that normally requires a trained regulatory affairs professional and a stack of open browser tabs.
Case Study: A 510(k) Strategy Skill in Action
To show what this looks like in practice, we built a 510(k) Regulatory Strategy Skill for Claude. Give it a device description, and it works through the same process an experienced regulatory strategist would:
- Search for predicate devices using NyquistAI's device and clearance data, filtering by product code, indications for use, and technological characteristics.
- Extract testing design details from FDA 510(k) summary files — the standards applied, acceptance criteria, and testing rationale used by comparable cleared devices.
- Generate a predicate comparison table, mapping similarities and differences across intended use, technology, and performance characteristics.
- Search relevant FDA guidance documents to ground the testing plan in current agency expectations.
- Generate a full testing requirements program — electrical safety, biocompatibility, software V&V, usability, acoustic output, and more, each with rationale and acceptance criteria.
- Formulate Pre-Submission (Q-Sub) questions, organized by priority, ready to bring to FDA.
We ran the Skill against a hypothetical device, a handheld cardiac ultrasound system we called "CardioView", and the output was a genuinely usable regulatory strategy report. In minutes, Claude:
- Identified Butterfly iQ3 (K232808) as the strongest primary predicate, with Butterfly iQ (K202406) as a supporting reference, after comparing several candidate clearances by product code, indications, and device description.
- Recommended IYN (Ultrasonic Pulsed Doppler Imaging System) as the primary product code, with IYO and ITX as secondary codes, reasoning from the predicate's own classification structure.
- Built out a full testing program spanning IEC 60601 series safety standards, IEC 60601-2-37 and NEMA UD-2/UD-3 for acoustic output, ISO 10993 biocompatibility testing, software verification per FDA's software guidance, and IEC 62366 usability validation — each tied back to what the predicate actually used.
- Drafted a prioritized list of Pre-Submission questions for FDA, covering predicate acceptability, product code confirmation, testing adequacy, and the proposed Indications for Use statement.
- Even sketched a realistic project timeline and testing budget, based on the predicate's own review history.
You can see the full example report here: CardioView 510(k) Strategy Report
This is the kind of deliverable that traditionally takes a regulatory consultant days or weeks to assemble.
We want to note it's just a starting draft, not a replacement for expert review. But as a first-pass strategy document to accelerate a team's thinking, or a way to stress-test an internal predicate assumption before committing budget, it changes the economics of early-stage regulatory planning entirely.
Why This Matters Beyond 510(k) Strategy
The 510(k) strategy Skill is just one example. The same pattern, structured FDA data + a defined expert workflow, applies across medtech regulatory and quality work:
- Competitive intelligence on a product code or therapeutic area
- Adverse event and MAUDE trend monitoring for post-market surveillance
- Warning letter and inspection citation analysis for quality system benchmarking
- Guidance document tracking as FDA policy evolves
Because NyquistAI's data is structured and MCP-accessible, any of these can become a Claude Skill: a repeatable, auditable process rather than a one-off prompt.
Try It Yourself
If your team is exploring how AI can support regulatory strategy, device intelligence, or quality operations, we'd love to show you what's possible. Contact the NyquistAI team to learn more about integrating NyquistAI's MCP server with Claude and to get setup instructions for your organization.