Minuteful-kidney test

K222921

Healthy.io Ltd. · cleared 2023-09-08 · product code JIR · Clinical Chemistry

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“The system consists of a smartphone application, proprietary Color-Board and an ACR Reagent Strip. The device also consists of an easy-to-use smartphone application, image recognition algorithms, and a physician compendium. The software component of the Minuteful - kidney test consists of both an application (app) and a backend server. Both components encompass different computer vision and machine learning algorithmic components, performing the image analysis activities.”
Algorithmimage recognition algorithms, computer vision and machine learning algorithmic components
source quote (p.5)
“The device also consists of an easy-to-use smartphone application, image recognition algorithms, and a physician compendium. The software component of the Minuteful - kidney test consists of both an application (app) and a backend server. Both components encompass different computer vision and machine learning algorithmic components, performing the image analysis activities.”
Adaptive (vs locked)No
source quote (p.7)
“Newly introduced smartphone-hardware and new operating systems will be validated by the company on a regular basis.”
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (7)

Bench

sample size not stated

endpoints: detection limits

standards: CLSI EP17-A2

Bench

sample size not stated

endpoints: performance not impacted by lighting conditions

Bench

sample size not stated

endpoints: performance not impacted by distance and angle conditions

Bench

sample size not stated

endpoints: performance not impacted by the presence of shadows

Bench

sample size not stated

endpoints: performance not impacted by image blur

Bench

sample size not stated

endpoints: performance not impacted by test strip placement

Bench

sample size not stated

endpoints: performance not impacted by dirty substances

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

6
recalls in product code, 24mo
2
MAUDE reports in code, 12mo
-14%
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Clinical Chemistry panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K222921