Cleared Traditional

K260300 - WatchMate Software

K260300 is an FDA 510(k) clearance for WatchMate Software, manufactured by Anumana, Inc.. The device is a Class 2 Radiology device with product code QIH cleared through the Traditional 510(k) pathway after a 136-day FDA review.

K260300 · Anumana, Inc. · Radiology device
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Optimized for regulatory review, auditing and printing
Jun 2026
Decision
136d
Days
Class 2
Risk

K260300 is an FDA 510(k) clearance for the WatchMate Software. Classified as Automated Radiological Image Processing Software within the QIH classification (a category dominated by AI-based automated radiology processing systems), Class II - Special Controls.

Submitted by Anumana, Inc. (Cambridge, US). The FDA issued a Cleared decision on June 15, 2026 after a review of 136 days - within the typical 510(k) review window.

This device falls under the Radiology FDA review panel, regulated under 21 CFR 892.2050 - the FDA radiology and imaging software oversight framework. The Traditional 510(k) pathway establishes clearance through substantial equivalence to a legally marketed predicate device, without requiring clinical trial data.

Device pattern: Incremental AI imaging tool. Moderate equivalence dependency. Overall, this clearance reflects a predicate-aligned approval typical of modern AI radiology extensions - not a novel clinical breakthrough, but a validated iteration within an established regulatory category.

View all Anumana, Inc. devices

FDA 510(k) Submission Details - K260300

510(k) Number K260300 FDA.gov
FDA Decision Cleared Substantially Equivalent - Traditional 510(k) (SESE)
Date Received January 30, 2026
Decision Date June 15, 2026
Days to Decision 136 days
Submission Type Traditional
Review Panel Radiology (RA)
Summary Summary PDF
Third-party Review No - reviewed directly by FDA
Combination Product No
PCCP Authorized No
Regulatory Context
Review time vs. panel average
29d slower than avg
Panel avg: 107d · This submission: 136d
Pathway characteristics
Predicate-based equivalence.

QIH Device Classification - Class 2, Special Controls

Product Code QIH Automated Radiological Image Processing Software
Device Class Class 2 - Special Controls
CFR Regulation 21 CFR 892.2050
Definition To Provide Automated Radiological Image Processing And Analysis Tools. Software Implementing Artificial Intelligence Including Nonadaptive Machine Learning Algorithms Trained With Clinical And/or Artificial Data. In These Devices, The Algorithm Training Data Typically Impacts Device Performance. Adaptive Ai Algorithms Are Not Within Scope Of This Product Code.
What this classification means

Class II devices require demonstration of substantial equivalence to a legally marketed predicate device. Clinical trial data may be submitted as supporting evidence to strengthen the substantial equivalence argument. Most Radiology devices follow this clearance model.

Regulatory Consultant

Veranex, Inc.
Michael Billig

The regulatory consultant manages the 510(k) submission process on behalf of the applicant - coordinating technical documentation, predicate strategy and FDA communications. Identifying the consultant behind a submission is a key signal for competitive regulatory intelligence.

Clinical Evidence

ClinicalTrials.gov
NCT07126600 Completed Observational Industry-sponsored

Data Collection for Echocardiography-Based Software Assessment

A Data Collection Study for Echocardiography-Based Software Assessment

100
Patients (actual)
6
Sites
Condition studied Atrial Fibrillation; Left Atrial Appendage Closure; Cardiovascular Diseases
Eligibility All sexes · 18 Years+
Principal investigator Leon Ptaszek, MD, PhD
Sponsor Anumana, Inc. (industry)
Started 2025-07-11 → Primary completion 2025-11-19 → Completed 2025-12-17
Primary outcome
Comparison of Imaging-Derived Measurements
Study completed - no results published. This trial concluded in 2025 but has not posted results to ClinicalTrials.gov. Completed studies without public results are common in industry-sponsored device trials; the data may be referenced in the 510(k) Summary PDF or remain unpublished. Individual participant data will not be shared.
View full study on ClinicalTrials.gov

Regulatory Peers - QIH Automated Radiological Image Processing Software

All 329
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