510(k) Predicate Finder
Find potential predicate devices for your 510(k) submission. Enter a K-number to find all clearances with the same product code, a three-letter product code to browse clearances directly, or search by device name.
Let the assistant find your predicates
Describe your device and the Research Assistant searches 510(k)s, compares intended use, and drafts a predicate shortlist — with citations.
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Scaffold, Partial Medial Meniscal Defects Extending Into The Red/White Zone, Resorbable Bovine Collagen
General, Plastic Surgery
The Scaffold for Partial Medial Meniscal Defects, Resorbable Bovine Collagen (product code OLC) is a Class 2 implantable device regulated under 21 CFR 878.3300 in the General, Plastic Surgery specialty (SU), cleared via 510(k). It is intended for surgical repair and reinforcement of soft tissue injuries of the medial meniscus in patients with an intact meniscal rim and with defects extending at least into the red/white zone of the meniscus to ensure sufficient vascularization. The device is resorbable and replaced by the patient's own soft tissue; it is flagged as an implant but is not life-sustaining.
510(k) Clearances
3 matchesWhat is a Predicate Device?
A predicate device is a legally marketed device that a new 510(k) applicant uses to demonstrate substantial equivalence. The FDA's 510(k) pathway requires manufacturers to show that their device has the same intended use and similar technological characteristics as one or more predicate devices already cleared for commercial distribution.
Finding the right predicate is a critical step in 510(k) strategy. Manufacturers typically search for cleared devices with the same FDA product code, which groups devices by their intended use and regulatory classification. This tool helps you identify potential predicates by browsing all clearances within a product code.
Note that predicate devices must be legally marketed — they cannot be devices that were cleared but never commercialized, or devices subject to a mandatory recall. The determination of substantial equivalence considers intended use, technological characteristics, and performance data.