Who we serve · Proposed role

Device / MedTech Professional

You work in device regulatory, clinical, or competitive intelligence. ClinicaLister pulls a device's full FDA picture — clearance, classification, GUDID identity, recalls, adverse events, and safety signals — onto one screen, cross-filters it with charts, and maps each device to the trials that reference it, so the five-lookup scavenger hunt is already done.

Where it wins

The highest-leverage things ClinicaLister does for a device / medtech professional.

The whole FDA device dossier on one screen. Clearance (510(k)/PMA), classification, GUDID attributes, recalls, adverse-event signals, and establishment registrations sit together in one device profile and roll up into cross-filtering charts — recall trends, adverse-event types, safety-signal detection, class, submission type, MRI safety — instead of the four or five separate FDA and GUDID lookups a single device used to take.

Predicate and recall history, read side by side. Predicate data and recall history live in the same view, so a reviewer can catch a predicate that was later recalled before building a 510(k) around it — the single most distinctive device insight, and one neither FDA's databases nor a trial registry gives you on its own.

Device-to-trial evidence mapping. Confidence-scored links connect each cleared device to the trials that actually reference it, answering "which of these devices has clinical evidence behind it, and where are the gaps" — a question the FDA databases and the trial registry can't answer separately.

The weekly work × ClinicaLister

Every recurring activity, mapped to what ClinicaLister does — on which surface (the App, the MCP graph, or both), the time it saves, and how confident that claim is.

Activity	What ClinicaLister does	Surface	Time saved	Confidence
Device competitive landscape by product code / advisory committee	Filter and roll up the full device table into a cross-filtering landscape by class, submission type, and advisory committee — every 510(k)/PMA cross-reference in one view.	Both	manual 510(k)/PMA cross-refs → one cross-filtering landscape	High
510(k) predicate selection & chain analysis	Surfaces predicate-device data and a chain analysis that flags the most-cited predicates and any chain contaminated by a later recall.	Both	predicate shortlist with contamination flag	Medium
Recall pattern & risk monitoring	Recall history and a recall-trend chart show exposure by class, firm, and reason over time.	Both	recall exposure by class/firm/reason + over-time trend	High
MAUDE post-market surveillance / AE trending	Adverse-event reports at three levels — this device, same manufacturer, and product code — tagged by malfunction, injury, and death and trended over time.	Both	AE trend without querying openFDA by hand	High
Safety-signal detection	Genuine disproportionality scoring at the product-code level surfaces adverse-event clusters as candidate signals.	Both	disproportionate AE clustering surfaced as candidates	Medium
GUDID product lookup (MRI, sterilization, latex, combination)	One panel of GUDID attributes — MRI safety, sterilization, latex, single-use, prescription status, and combination/kit flags — instead of a lookup per device identifier.	Both	instant attribute lookup vs AccessGUDID per DI	High
Device-trial evidence mapping / Class III gaps	Confidence-scored device-to-trial links show which devices have clinical evidence and which lack it.	Both	which devices have trial evidence and which lack it	High
Regulatory pathway / classification profile	The full classification profile — class, implant and life-sustaining flags, regulation number, decision code and date, and expedited-review status — sits beside the device.	Both	full regulatory profile beside the device	High
Establishment / registration intelligence	Registered establishments by product code, with firm name and location, read as a manufacturing-footprint and competitor-presence signal.	Both	manufacturing-footprint / competitor-presence signal	Medium
Combination-product screening	Identifies combination products and lists their constituent components.	MCP	identifies combination devices and their parts	Medium
Competitor device tracking (new clearances / supplements)	Filter by applicant, trade name, and decision date, then auto-follow a firm or product code to watch clearance activity without re-running searches.	Both	watches clearance activity without weekly re-runs	Medium
Run a full sourced device report via agent	Your AI assistant assembles a decision-ready, source-attributed device intelligence report on request.	MCP	decision-ready, source-attributed report	High

What we don't do (yet)

Straight answers on where ClinicaLister stops today — so there are no surprises.

US-FDA and GUDID-centric. Device coverage is built on US FDA and GUDID data — there's no EU MDR / EUDAMED, CE-mark, or notified-body depth.

Public FDA data only. No internal complaint database, CAPA / QMS / eQMS, or design-history-file content — this is decision support, not a quality system.

Recall and designation data can lag. A clean recall result for one product code isn't proof a device is recall-free, and the expedited-review flag can miss a live breakthrough designation — cross-check the specific device against FDA's recall and breakthrough lists before a go/no-go decision.

Adverse-event surveillance carries reporting bias. Counts reflect voluntary and mandatory reports with under- and over-reporting, and disproportionality scores flag candidates, not confirmed causal findings.

Not a submission or quality system. No 510(k)/PMA authoring, eSTAR, or GUDID data entry, and no system of record for filings — and device-to-trial links are confidence-scored suggestions, not asserted facts.

The whole FDA device dossier on one screen — 510(k)/PMA clearance, classification, GUDID identity, recalls, adverse-event signals, and registrations — with predicate-and-recall analysis and confidence-scored links from each device to the trials that cite it.

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