Minuteful-kidney test

Healthy.io Ltd. • Clinical Chemistry • 09/08/2023

510(k)IEC 62304 Class B

Device Purpose

The Minuteful - kidney test is a home-use in-vitro diagnostic system designed for individuals at risk of kidney disease to semi-quantitatively measure urinary albumin and creatinine, and calculate the ACR. It utilizes a smartphone application with computer vision and machine learning algorithms to analyze an ACR Reagent Strip against a proprietary Color-Board via reflectance photometry, with an Image Validation Transfer System ensuring broad device compatibility and robust performance under various home-use conditions.

Summary

The Minuteful - kidney test is a prescription-only, in-vitro diagnostic system designed for home use by individuals at risk of kidney disease. Its primary function is the semi-quantitative measurement of albumin and creatinine in urine, subsequently calculating and presenting the albumin-creatinine ratio (ACR). This system comprises a kit containing a urine receptacle, an ACR Reagent Strip, an absorbing pad, and a proprietary Color-Board, along with a user-friendly smartphone application that guides the user through the testing process. The results are intended to aid in assessing kidney health when used in conjunction with clinical evaluation. The system employs reflectance photometry for detection, utilizing a photosensitive diode and URiSCAN 2ACR urine strips to analyze the analytes albumin and creatinine after a 75-second incubation. The core technology involves a smartphone application and a backend server, which incorporate computer vision and machine learning algorithms for image analysis of the reagent strip against the Color-Board. A key feature is the Image Validation Transfer System (IVTS), ensuring compatibility across a wide range of smartphones and operating systems. Performance data for this modified device (K222921) confirmed its robustness through studies on Limit of Detection and various IVTS challenges, including varied illumination, physical misalignments, shadows, blurriness, misplaced strips, and dirty Color-Boards, all showing no impact on performance within supported conditions. Other performance characteristics like precision and clinical performance rely on data from its predicate (K210069).

AI Regulatory Concerns

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

Keywords

Albumin-Creatinine Ratio (ACR)Home-use testSmartphone applicationUrine analysisKidney diseaseSemi-quantitative measurementComputer visionMachine learningReflectance photometryImage Validation Transfer System (IVTS)

Device Metadata

Submission Number

K222921

Company

Healthy.io Ltd.

Panel

Clinical Chemistry

Product Code

N/A

Data Type

Images

Clinical Function

Assessment

AI Function

Analysis

AI Subclass

quantification/feature localization

Relevant Clinical Questions

Q1. How does the Image Validation Transfer System (IVTS) specifically ensure accuracy across diverse smartphone camera qualities and ambient lighting conditions encountered in a home setting?; What are the specific ranges for "semi-quantitative" measurements of albumin and creatinine, and how do these correlate with established clinical thresholds for kidney disease assessment?; Given that precision and clinical performance data are referenced from the predicate device (K210069), were any bridging studies conducted to confirm these aspects specifically for the K222921 modifications, particularly regarding the updated IVTS?; How does the system handle potential user errors during sample collection or strip handling that are not related to image capture (e.g., incorrect dip time, contamination)?; What are the data security and privacy measures implemented for the transfer and storage of sensitive health information via the smartphone application and backend server, especially when integrating with EMRs?

Risk Classification

ESL Analysis

IEC 62304 ClassB

FDA Device ClassII

FDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Authorized before §524B enforcement

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Cybersecurity Evidence

Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.

Cyber Score55/100

SBOM Evidence⚠ Not mentioned in summary

Cyber Risk Assessment✓ Detected in Summary

Postmarket Plan✓ Detected in Summary

§524B ApplicableNo

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials

- Not detected

ML-BOMMachine Learning Bill of Materials(machine learning, algorithm)

✓ Detected

SaaSBOMSoftware-as-a-Service Bill of Materials(server, backend)

✓ Detected

HBOMHardware Bill of Materials(camera)

✓ Detected

CBOMCryptography Bill of Materials

- Not detected

VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange

- Not detected

OBOMOperations Bill of Materials(environment)

✓ Detected

Analysis:

• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.

• Evidence of ML-BOM, SaaSBOM, HBOM, OBOM detected in AI-generated device summary.

• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.

• Not detected in AI-generated device summary: SBOM, CBOM, VDR/VEX. These may be present in the full FDA submission.

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