Computer vision and machine learning image analysis
—
92.7% exact agreement
—
—
Clinical trial: >450 subjects
—
Albumin
Computer vision and machine learning image analysis
—
92.1% exact agreement
—
—
Clinical trial: >450 subjects
—
Creatinine
Computer vision and machine learning image analysis
—
88.2% exact agreement
—
—
Clinical trial: >450 subjects
—
Indications for Use
The Minuteful - kidney test is an in-vitro diagnostic, home-use urine analysis test system for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The system consists of a smartphone application, proprietary Color-Board and an ACR Reagent Strip. The system is available for prescription-use only and is intended for people at risk of kidney disease. Results are intended to be used in conjunction with clinical evaluation as an aid in the assessment of kidney health.
Device Story
The Minuteful-Kidney Test is a home-use diagnostic system for assessing kidney health. It utilizes a YD Diagnostics URiSCAN 2 ACR urine strip, a proprietary Color-Board, and a smartphone application. The user collects a midstream urine sample, dips the test strip, and places it on the Color-Board. The smartphone camera captures an image of the strip and board; a cloud-based image recognition algorithm analyzes the color changes on the reagent pads. The system provides semi-quantitative results for albumin, creatinine, and the albumin-creatinine ratio (ACR). ACR results are displayed to the user and the physician, while individual analyte results are reported only to the physician. The application guides the user through the process and enforces quality checks (e.g., lighting, focus, strip placement, and assay timing) to ensure valid results. This allows patients at risk of kidney disease to monitor their status remotely, facilitating clinical decision-making by their healthcare providers.
Clinical Evidence
Clinical study involved >450 subjects comparing lay-user results from the Minuteful - kidney test against professional-user results from the URISCAN Optima analyzer. Primary endpoints included accuracy and usability. Results showed 92.7% exact agreement for ACR, 92.1% for albumin, and 88.2% for creatinine, with 100% agreement within ±1 color block for all analytes. Usability testing showed 100% of subjects completed the test on the first attempt without issues. Analytical performance was validated via CLSI guidelines (EP05-A3, EP07, EP17-A2, EP6-A), showing 100% repeatability and reproducibility.
Technological Characteristics
System uses reflectance photometry via smartphone camera and proprietary Color-Board. Employs URISCAN 2ACR urine strips. Software includes computer vision and machine learning algorithms for image analysis. Platform-agnostic via Image Validation Transfer System (IVTS). Connectivity via smartphone internet to backend server. Environmental stability tested per IEC TR 60721-4-1:2001+A1:-3 (Class 2K2, 2M3).
Indications for Use
Indicated for prescription-use by individuals at risk of kidney disease for home-based semi-quantitative measurement of urine albumin, creatinine, and albumin-creatinine ratio (ACR) to aid in the assessment of kidney health.
Regulatory Classification
Identification
A urinary protein or albumin (nonquantitative) test system is a device intended to identify proteins or albumin in urine. Identification of urinary protein or albumin (nonquantitative) is used in the diagnosis and treatment of disease conditions such as renal or heart diseases or thyroid disorders, which are characterized by proteinuria or albuminuria.
Predicate Devices
URiSCAN Optima urine chemistry test system (K141874)
Submission Summary (Full Text)
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FDA
U.S. FOOD & DRUG
ADMINISTRATION
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
ASSAY AND INSTRUMENT
## I Background Information:
A 510(k) Number
K210069
B Applicant
Healthy.io Ltd.
C Proprietary and Established Names
Minuteful- Kidney Test
D Regulatory Information
| Product Code(s) | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| JFY | Class II | 21 CFR 862.1225 - Creatinine test system | CH - Clinical Chemistry |
| JIR | Class I | 21 CFR 862.1645 - Urinary Protein Or Albumin (Nonquantitative) Test System | CH - Clinical Chemistry |
| KQO | Class I | 21 CFR 862.2900 - Automated urinalysis system | CH - Clinical Chemistry |
## II Submission/Device Overview:
A Purpose for Submission:
New Device
B Measurand:
Albumin and Creatinine in urine
C Type of Test:
Semi-quantitative urinalysis
Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993-0002
www.fda.gov
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K210069 - Page 2 of 17
# III Intended Use/Indications for Use:
## A Intended Use(s):
See Indications for Use below.
## B Indication(s) for Use:
The Minuteful - kidney test is an in-vitro diagnostic, home-use urine analysis test system for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). The system consists of a smartphone application, proprietary Color-Board and an ACR Reagent Strip. The system is available for prescription-use only and is intended for people at risk of kidney disease. Results are intended to be used in conjunction with clinical evaluation as an aid in the assessment of kidney health.
## C Special Conditions for Use Statement(s):
Rx - For Prescription Use Only
For In Vitro Diagnostics Use Only
## D Special Instrument Requirements:
The following representative smartphone models and operating system (OS) versions were used in different studies as described in Section VII Performance Characteristics.
| Manufacturer | Model | OS† version |
| --- | --- | --- |
| Apple | iPhone 11 | iOS 13 |
| Apple | iPhone 13 | iOS 15 |
| Apple | iPhone 7 | iOS 12 |
| Apple | iPhone 12 Pro MAX | iOS 14 |
| Apple | iPhone SE | iOS 15 |
| Google | Pixel 3a | Android 11 |
| LG | G5 | Android 6 |
| Motorola | G100 | Android 11 |
| Motorola | G10 | Android 11 |
| Nokia | 5.3 | Android 11 |
| OnePlus | 3 | Android 8 |
| Samsung | S21 Ultra | Android 11 |
| Samsung | Z Flip 3 | Android 11 |
| Samsung | note 8 | Android 8 |
| Samsung | a02s | Android 11 |
| Samsung | S9 | Android 10 |
†Operating System
Phones and OS versions that are not compatible with the Minuteful – kidney test will be blocked from downloading the application.
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## IV Device/System Characteristics:
### A Device Description:
The device is provided as a kit that comprises a single YD Diagnostics URiSCAN 2 ACR Urine strips (YD Diagnostics Corporation, k141874), 1 single-use Color-Boards, and a User Manual. The Minuteful – kidney test also consists of a smartphone application for use on the home users’ smartphone, and an image recognition algorithm running on a back-end, cloud-based server.
ACR results are reported to both the home user and the prescribing physician.
The individual albumin and creatinine results are reported only to the prescribing physician.
### B Principle of Operation:
The albumin test is based on sulfonephthalein dye binding to albumin at a constant pH. The development of pale green to aqua blue indicates the presence of albumin. The creatinine test is based on the peroxidase-like activity of a copper creatinine complex that catalyzes the reaction of diisopropylbenzene dihydroperoxide and 3,3’,5,5’- tetramethylbenzidine. The resulting color ranges from orange through green to blue.
The Minuteful – kidney test scans and analyzes the test strip using a mobile device running the smartphone application.
### C Instrument Description Information:
1. Instrument Name:
Minuteful - kidney test
2. Specimen Identification:
The Minuteful kidney-test application will instruct the user to enter their patient identification information in the application.
3. Specimen Sampling and Handling:
The test is performed using midstream urine sample collected in a cup.
4. Calibration:
Calibration is not needed.
5. Quality Control:
The device has internal controls and no external quality controls are provided.
## V Substantial Equivalence Information:
### A Predicate Device Name(s):
URiSCAN Optima urine chemistry test system
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B Predicate 510(k) Number(s):
K141874
C Comparison with Predicate(s):
| Device & Predicate Device(s): | K210069 | K141874 |
| --- | --- | --- |
| Device Trade Name | Minuteful - kidney test | URiSCAN Optima urine chemistry test system |
| General Device Characteristic Similarities | | |
| Intended Use/Indications For Use | Intend for the semi-quantitative measurement of albumin and creatinine in urine, as well as the presentation of their ratio, the albumin-creatinine ratio (ACR). | Same |
| Test Specimen | Urine | Same |
| General Device Characteristic Differences | | |
| Intended User | Lay user | Professional user |
| Environment Used | Home environment | Laboratories/Clinical |
VI Standards/Guidance Documents Referenced:
- Clinical and Laboratory Standards Institute (CLSI) EP05-A3 Evaluation of Precision of Quantitative Measurement Procedures, Approved Guidelines, Third Edition
- CLSI EP07: Interference Testing in Clinical Chemistry, Third Edition
- CLSI EP37: Supplemental Tables for Interference Testing in Clinical Chemistry – First Edition
- CLSI EP17-A2: Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures, Approved Guideline, Second Edition
- ANSI AAMI IEC, 62366-1: 2015+AMD1:2020: Medical devices Part 1: Application of usability engineering to medical devices
- ANSI AAMI IEC, 62304:2006/A1:2016, Medical device software-Software life cycle Processes
- ISO 14971:2019, Medical devices- Application of risk management to medical devices
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VII Performance Characteristics (if/when applicable):
A Analytical Performance:
1. Precision/Reproducibility:
Testing was conducted with 3 urine samples. Each urine sample was produced by spiking negative urine with albumin and creatinine to the following expected reporting levels: 10 mg/L, 30-80 mg/L, and 150 mg/L albumin; 10 mg/dL, 50 mg/dL, and 200-300 mg/dL creatinine; Normal, Abnormal, and High-Abnormal ACR. Testing was conducted by 3 operators over 3 days at 3 sites using 3 device lots per site. Each device lot was used to test each of the 3 urine samples in 2 runs per day with 3 replicates per run. All testing was conducted with 1 iPhone 11 and 1 Pixel 3a per site. Repeatability was calculated using the results from all of the replicates from the first run of the first day. Reproducibility was calculated using all replicates across the entire study.
Repeatability (iPhone 11 and Pixel 3a results combined)
| ACR | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | Normal | Abnormal | High-Abnormal | Overall | Overall 95% CI Low | Overall 95% CI High |
| Exact Match | Count | 54 | 54 | 54 | 162 | 97.8 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| ±1 Color Block | Count | 54 | 54 | 54 | 162 | 97.8 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| Albumin | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | 10 mg/L | 30-80 mg/L | 150 mg/L | Overall | Overall 95% CI Low | Overall 95% CI High |
| Exact Match | Count | 54 | 54 | 54 | 162 | 97.8 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| ±1 Color Block | Count | 54 | 54 | 54 | 162 | 97.8 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
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| Creatinine | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | 10 mg/dL | 50 mg/dL | 200-300 mg/dL | Overall | Overall 95% CI Low | Overall 95% CI High |
| Exact Match | Count | 54 | 54 | 54 | 162 | 97.8 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| ±1 Color Block | Count | 54 | 54 | 54 | 162 | 97.8 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
Reproducibility (iPhone 11 and Pixel 3a results combined)
| ACR | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | Normal | Abnormal | High-Abnormal | Overall | Overall 95% CI Low | Overall 95% CI High |
| Exact Match | Count | 324 | 324 | 324 | 972 | 99.6 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| ±1 Color Block | Count | 324 | 324 | 324 | 972 | 99.6 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| Albumin | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | 10 mg/L | 30-80 mg/L | 150 mg/L | Overall | Overall 95% CI Low | Overall 95% CI High |
| Exact Match | Count | 324 | 324 | 324 | 972 | 99.6 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| ±1 Color Block | Count | 324 | 324 | 324 | 972 | 99.6 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| Creatinine | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | 10 mg/dL | 50 mg/dL | 200-300 mg/dL | Overall | Overall 95% CI Low | Overall 95% CI High |
| Exact Match | Count | 324 | 324 | 324 | 972 | 99.6 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
| ±1 Color Block | Count | 324 | 324 | 324 | 972 | 99.6 | 100 |
| | % | 100% | 100% | 100% | 100% | | |
In addition to the studies described above, the sponsor also conducted a 20-day precision study in which spiked urine samples with 3 levels of albumin (expected values $10\mathrm{mg / L}$ , 30-
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80 mg/L, and 150 mg/L), creatinine (expected values 10 mg/dL, 50 mg/dL, 200-300 mg/dL), and ACR (Normal, Abnormal, and High-Abnormal) were tested by 3 operators in singlicate at 3 sites with 2 runs per day using 3 device lots with 1 iPhone and 1 Pixel 3a per site. The results were similar to the results in the studies described above.
# 2. Linearity:
Testing was conducted with urine samples spiked to 4 levels of creatinine (expected outputs of 10, 50, 100, and $200 - 300\mathrm{mg / dL}$ ), 3 levels of albumin (expected outputs of 10, 30-80, and $150\mathrm{mg / L}$ ), and 3 levels of ACR (expected outputs of Normal, Abnormal, and High-Abnormal). The study was performed by three (3) different operators, using three (3) different strip lots with ten (10) replicates per lot. The study was conducted using iPhone 11 and Pixel 3a devices.
| Albumin-Creatinine Ratio | | |
| --- | --- | --- |
| ACR Output | % Exact Match | % ±1 Color Block |
| Normal | 100 | 100 |
| Abnormal | 100 | 100 |
| High-Abnormal | 100 | 100 |
| Albumin | | |
| --- | --- | --- |
| ALB Output (mg/L) | % Exact Match | % ±1 Color Block |
| 10 | 100 | 100 |
| 30-80 | 100 | 100 |
| 150 | 100 | 100 |
| Creatinine | | |
| --- | --- | --- |
| CRE Output (mg/dL) | % Exact Match | % ±1 Color Block |
| 10 | 100 | 100 |
| 50 | 100 | 100 |
| 100 | 100 | 100 |
| 200-300 | 100 | 100 |
# 3. Analytical Specificity/Interference:
Interference testing was conducted per recommendations in CLSI EP07 Interference Testing in Clinical Chemistry; Approved Guideline - Third Edition. Negative urine was spiked with 3 levels of albumin (expected outputs of 10, 30-80, and $150\mathrm{mg / L}$ ) and creatinine (expected outputs of 10, 50, and $200 - 300\mathrm{mg / dL}$ ) to produce test samples with 3 levels of ACR (expected outputs of Normal, Abnormal, and High-Abnormal). Test samples were spiked with interfering substance or the same volume of diluent (control samples). The concentrations of interfering substances tested were higher than the concentrations of these substances expected to be in urine samples from the intended use population. Testing was conducted with 1 device lot on the Apple iPhone 11 and Google Pixel 3a and 10 replicates
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were tested at each test level with each potentially interfering substance. The results of the test samples with interfering substance were compared to the results of the control samples and no interference was defined as 100% agreement (10/10) between the sample with potential interferent and control samples. If interference was observed, additional testing was conducted to determine the lowest concentration of the interfering substance that shows interference and the highest that does not show interference.
The results of the interference study are summarized below.
| Potential Interfering Substance | Measurand | Highest Concentration of Potentially Interfering Substance at Which no Interference Observed |
| --- | --- | --- |
| Acetominophen | ACR | 300 mg/dL |
| | Albumin | 300 mg/dL |
| | Creatinine | 300 mg/dL |
| Albumin | ACR | N/A |
| | Albumin | N/A |
| | Creatinine | 880 mg/dL |
| Ascorbic Acid | ACR | 440 mg/dL |
| | Albumin | 440 mg/dL |
| | Creatinine | 220 mg/dL |
| Bilirubin | ACR | 6 mg/dL |
| | Albumin | 6 mg/dL |
| | Creatinine | 6 mg/dL |
| Caffeine | ACR | 37 mg/dL |
| | Albumin | 37 mg/dL |
| | Creatinine | 37 mg/dL |
| Blood | ACR | 0.05% |
| | Albumin | 0.05% |
| | Creatinine | 0.05% |
| Calcium Chloride | ACR | 210 mg/dL |
| | Albumin | 210 mg/dL |
| | Creatinine | 210 mg/dL |
| Capotopril | ACR | 12 mg/dL |
| | Albumin | 12 mg/dL |
| | Creatinine | 12 mg/dL |
| Citric Acid | ACR | 100 mg/dL |
| | Albumin | 100 mg/dL |
| | Creatinine | 100 mg/dL |
| Creatinine | ACR | N/A |
| | Albumin | 750 mg/dL |
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| Potential Interfering Substance | Measurand | Highest Concentration of Potentially Interfering Substance at Which no Interference Observed |
| --- | --- | --- |
| | Creatinine | N/A |
| Cyanocobalamin (Vitamin B12) | ACR | 0.16 mg/dL |
| | Albumin | 0.16 mg/dL |
| | Creatinine | 0.16 mg/dL |
| Dapagliflozin | ACR | 0.03 mg/dL |
| | Albumin | 0.03 mg/dL |
| | Creatinine | 0.03 mg/dL |
| Fructose | ACR | 100 mg/dL |
| | Albumin | 100 mg/dL |
| | Creatinine | 100 mg/dL |
| Glucose | ACR | 5000 mg/dL |
| | Albumin | 5000 mg/dL |
| | Creatinine | 5000 mg/dL |
| Glycine | ACR | 450 mg/dL |
| | Albumin | 450 mg/dL |
| | Creatinine | 450 mg/dL |
| Hemoglobin | ACR | 6.8 mg/dL |
| | Albumin | 6.8 mg/dL |
| | Creatinine | 6.8 mg/dL |
| Hydrochlorothiazide | ACR | 5 mg/dL |
| | Albumin | 5 mg/dL |
| | Creatinine | 5 mg/dL |
| Hydroxychloroquine sulfate | ACR | 4 mg/dL |
| | Albumin | 4 mg/dL |
| | Creatinine | 8 mg/dL |
| Iron Sulfate | ACR | 24 mg/dL |
| | Albumin | 24 mg/dL |
| | Creatinine | 24 mg/dL |
| Acetoacetic Acid | ACR | 300 mg/dL |
| | Albumin | 300 mg/dL |
| | Creatinine | 300 mg/dL |
| Leukocytes | ACR | 2500 leukocytes/μL |
| | Albumin | 2500 leukocytes/μL |
| | Creatinine | 2500 leukocytes/μL |
| Losartan | ACR | 5 mg/dL |
| | Albumin | 5 mg/dL |
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| Potential Interfering Substance | Measurand | Highest Concentration of Potentially Interfering Substance at Which no Interference Observed |
| --- | --- | --- |
| | Creatinine | 5 mg/dL |
| Metformin Hydrochloride | ACR | 285 mg/dL |
| | Albumin | 285 mg/dL |
| | Creatinine | 285 mg/dL |
| Phenolphthalein | ACR | 1060 mg/dL |
| | Albumin | 1060 mg/dL |
| | Creatinine | 1060 mg/dL |
| Potassium Chloride | ACR | 1990 mg/dL |
| | Albumin | 1990 mg/dL |
| | Creatinine | 1990 mg/dL |
| Riboflavin | ACR | 20 mg/dL |
| | Albumin | 20 mg/dL |
| | Creatinine | 20 mg/dL |
| Sodium Acetate | ACR | 260 mg/dL |
| | Albumin | 260 mg/dL |
| | Creatinine | 260 mg/dL |
| Sodium Bicarbonate | ACR | 975 mg/dL |
| | Albumin | 975 mg/dL |
| | Creatinine | 975 mg/dL |
| Sodium Chloride | ACR | 5100 mg/dL |
| | Albumin | 5100 mg/dL |
| | Creatinine | 5100 mg/dL |
| Sodium Nitrite | ACR | 9 mg/dL |
| | Albumin | 9 mg/dL |
| | Creatinine | 9 mg/dL |
| Sodium-2-mercaptoethanesulfonate (Mesna) | ACR | 750 mg/dL |
| | Albumin | 750 mg/dL |
| | Creatinine | 190 mg/dL |
| Theophylline | ACR | 100 mg/dL |
| | Albumin | 100 mg/dL |
| | Creatinine | 100 mg/dL |
The sponsor is including the table below with the statement "In addition, the ACR result may be falsely elevated in patients taking sodium bicarbonate and/or hydroxychloroquine in high concentrations" in the Physician Compendium to describe the impact of the observed interferences on the device.
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| Analyte/ measurand | Interfering substance | Lowest tested concentration causing an interference | Interference effect |
| --- | --- | --- | --- |
| Albumin | Sodium bicarbonate | 1,300 mg/dL | Falsely increased |
| | Hydroxychloroquine sulfate | 6 mg/dL | |
| Creatinine | Mesna | 380 mg/dL | Falsely decreased |
| | Ascorbic acid | 330 mg/dL | |
| | Sodium bicarbonate | 1,300 mg/dL | |
| ACR | Sodium bicarbonate | 1,300 mg/dL | Falsely increased |
| | Hydroxychloroquine sulfate | 6 mg/dL | |
To inform the lay user about potential interference, the User Manual contains the statements, "Do not use the device in the case of a discolored urine specimen. If the color of your urine is different than yellow or clear, do not use this test and consult with your healthcare professional" and "The substances that have been shown to interfere include: Ascorbic acid (Vitamin C), mesna (MESNEX), sodium bicarbonate and hydroxychloroquine sulfate (PLAQUENIL®). If you are taking these medications or supplements, please inform your physician."
## Specific Gravity (SG)
The test urine samples were adjusted to specific gravities of 1.000, 1.005, 1.010, 1.015, 1.025, 1.035, and 1.045. No interference on albumin, creatinine or ACR was observed at the urine specific gravities tested.
## pH
The test urine samples were adjusted to pH levels of 4, 5, 6, 7, 8, and 9. No interference on albumin, creatinine or ACR was observed at the urine pH levels tested.
4. Traceability, Stability, Expected Values (Controls, Calibrators, or Methods):
The sponsor's device is traceable to a legally marketed urine ACR device. The sponsor's traceability scheme was reviewed and found acceptable.
5. Detection Limit/Cutoffs:
The sponsor collected a total of 57 urine samples from subjects with Diabetes Mellitus Type II, Hypertension, Dyslipidemia, Cardiovascular disease, a known kidney disease (e.g., Nephrolithiasis, Congenital abnormalities of the kidney and urinary tract, Diabetic nephropathy), Malignancy (e.g., Renal cell carcinoma), Autoimmune disease and Tobacco use disorder. The median age of this population was 62. The samples were pooled and diluted with negative urine to produce different levels of albumin and creatinine. Albumin and creatinine were measured in test samples using a commercially available device that quantitatively measures albumin and creatinine in urine.
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The sponsor conducted testing with 1 lot of their device. Several samples with albumin and creatinine levels around the cutoffs were tested and the sponsor used a Probit model described in the CLSI EP17-A2 guideline to estimate the C5, C50 and C95 for each of the cutoffs. Testing was conducted with 16 representative smartphones.
The sponsor's study supports that the cutoffs between the albumin and creatinine categories are the same when the test is used with different smartphones and operating systems.
6. Assay Cut-Off:
Not Applicable.
7. Accuracy (Instrument):
See Section B.1. Method Comparison
8. Carry-Over:
See Section F. Other Supportive Instrument Performance Characteristics Data
B Comparison Studies:
1. Method Comparison with Predicate Device:
A total of 466 subjects (263 males and 203 females) 18 to 81 years of age were enrolled to assess the performance of the sponsor's device. Study subjects were lay users and included those with hypertension, Type 2 Diabetes, dyslipidemia, cardiovascular disease and kidney disease. Subjects tested their own urine samples with the sponsor's device using an iPhone 11 or Google Pixel 3a following the user manual and in-application prompts. The subjects' urine samples were then tested by a trained operator using the predicate device. The trained operator was blinded to the results from the sponsor's device. The results from the sponsor's device were compared with the results from the predicate device. The results are summarized in the tables below.
| ACR | Comparator device | | | | |
| --- | --- | --- | --- | --- | --- |
| Minuteful Kidney test | Reported block | Normal | Abnormal | High Abnormal | Total |
| | Normal | 254 92.0% | 5 3.0% | - | 259 |
| | Abnormal | 22 8.0% | 158 94.0% | 2 9.1% | 182 |
| | High Abnormal | - | 5 3.0% | 20 90.9% | 25 |
| | Total | 276 | 168 | 22 | 466 |
| | Exact match | 92% | 94% | 90.9% | 92.7% |
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| Albumin | Comparator Device | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Minuteful - Kidney Test | Reported blocks | 10 | 30 | 80 | 150 | Total |
| | 10 | 220
92.8% | 2
2.4% | - | - | 222 |
| | 30,80 | 17
7.2% | 82
97.6% | 67
84.8% | 6
9.1% | 172 |
| | 150 | - | - | 12
15.2% | 60
90.9% | 72 |
| | Total | 237 | 84 | 79 | 66 | 466 |
| | Exact Match | 92.8% | 91.4% | | 90.9% | 92.1% |
| Creatinine | Comparator Device | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Minuteful - Kidney Test | Reported blocks | 10 | 50 | 100 | 200 | 300 | Total |
| | 10 | 43
95.6% | 9
5.8% | - | - | - | 52 |
| | 50 | 2
4.4% | 139
89.7% | 16
9.2% | - | - | 157 |
| | 100 | - | 7
4.5% | 145
83.3% | 7
22.6% | 1
1.6% | 160 |
| | 200,300 | - | - | 13
7.5% | 24
77.4% | 60
98.4% | 97 |
| | Total | 45 | 155 | 174 | 31 | 61 | 466 |
| | Exact Match | 95.6% | 89.7% | 83.3% | 91.3% | | 88.2% |
## Usability Results
All 466 study participants (100%) completed the Minuteful - kidney test using only the user manual provided in the kit and the device in-app guides to test their own urine. The subjects rated the overall ease of use of the Minuteful - kidney test on a scale of 1 (very hard) to 5 (very easy) and the average ease-of-use rating was 4.93, indicating that the subjects found the test easy to use.
## 2. Matrix Comparison:
Not applicable. This test is only for urine samples.
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C Clinical Studies:
1. Clinical Sensitivity: Not Applicable
2. Clinical Specificity: Not Applicable
3. Other Clinical Supportive Data (When 1. and 2. Are Not Applicable): See Section B.1. Method Comparison with Predicate
D Clinical Cut-Off: Not Applicable
E Expected Values/Reference Range:
Minuteful - kidney test ACR Results
| | Normal | Abnormal | High Abnormal |
| --- | --- | --- | --- |
| Albumin-Creatinine Ratio | < 30 [mg/g] / 3.4 [mg/mmol] | 30-300 [mg/g] / 3.4-33.9 [mg/mmol] | > 300 [mg/g] / 33.9 [mg/mmol] |
Albuminuria categories are based on ACR (mg albumin per gram of creatinine in a spot urine sample). Categories are based on recommendations in Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney inter., Suppl. 2013; 3: 1–150.
F Other Supportive Instrument Performance Characteristics Data:
The sponsor conducted flex studies with urine samples spiked with albumin and creatinine to three levels of albumin, creatinine, and ACR. The expected results for the three levels of urine samples tested were 10 mg/L, 30-80 mg/L, and 150 mg/L for albumin; 10 mg/dL, 50 mg/dL, and 200-300 mg/dL for creatinine; Normal, Abnormal, and High-abnormal for ACR.
1. Timing
a) Dipping Time
Strips were dipped in the test urine samples for two different time durations, 1 second (the control dipping time) and 10 seconds. Wetting ("blotting") and assay times (time between blotting and scanning) were <1 second and 75 seconds, respectively. Testing was conducted with two representative smartphones of different models and operating systems (iPhone 11 and Pixel 3a). The results support that dipping for up to 10 seconds does not impact test performance. The Minuteful kidney – test application guides the user through each step of the testing procedure and instructs the user to dip the strip for 1 second.
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b) Blotting Time
Strips were dipped in the test urine samples for 1 second and either blotted for <1 second (control) or blotted for 75 seconds (test). Testing was conducted with two representative smartphones of different models and operating systems (iPhone 11 and Pixel 3a). The results support that blotting times for up to 75 seconds do not impact test performance. The Minuteful kidney – test application guides the user through each step of the testing procedure and instructs the user to blot the strip for 1 second.
c) Assay Time
Strips were dipped in the test urine samples for 1 second and blotted for <1 second. The assay time (time between blotting and scanning the strip with the smart phone) were 75 seconds (the control assay time) and 180 seconds (test assay time). Testing was conducted with two representative smartphones of different models and operating systems (iPhone 11 and Pixel 3a). The results support that assay times for up to 180 seconds do not significantly impact test performance. The Minuteful kidney – test application guides the user through each step of the testing procedure and instructs the user to take a picture of the test strip and Color-Board within 3 minutes (180 seconds) of blotting the test strip. If the assay time exceeds 180 seconds, the application prevents the user from completing the test.
2. Carry-Over
Strips were held in both the "up" (with albumin on top) and "down" (with creatinine on top) positions for 0 (control), 10, 25 and 40 seconds after being dipped in solutions and before blotting. In the "up" experiment, a solution comprised of 150 mg/L albumin and 10 mg/dL creatinine, was used. In the "down" experiment, a solution comprised of 200-300 mg/dL creatinine and 10 mg/L albumin, was used. Dipping and assay times were 1 and 75 seconds, respectively. The wetting ("blotting") time corresponded to the time the strip will be held in the "up" or "down" position (nested factors). Testing was conducted with two representative smartphones of different models and operating systems (iPhone 11 and Pixel 3a). The results support that the performance is not impacted by potential carry-over from one reagent pad to the other. The Minuteful kidney – test application guides the user through each step of the testing procedure and instructs the user to blot the test strip immediately after dipping and place it on the Color-Board.
3. Illumination
a) Testing was conducted under different lighting conditions of different color "temperatures" and intensities from different light sources representative of those that may be used in the home setting. Testing was conducted with 16 representative smart phones of different models using different operating systems. The results of the study support that the performance is not impacted by lighting conditions that are likely to be found in the home use environment.
b) Testing was conducted under different lighting conditions with different saturation of red, green, and blue light. Testing was conducted with 16 representative phones of different models and operating systems. Phones were tested under "boundary conditions" that were
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the maximum saturation of red, green, or blue light under which the device allowed the phone to take a picture of the urine test strip and color-board (under red, green, or blue light saturation that exceeded the boundary conditions, the application blocks the user from taking a picture). The results of this testing support that the device performance is not impacted by different light color saturation.
c) Testing was conducted under different light intensities (darkness and brightness measured in lux). Testing was conducted with 16 representative phones of different models and operating systems. Phones were tested under “boundary conditions” of light intensity that were the minimum light intensity and the maximum light intensity at which the device allows the phone to take a picture of the color board and urine test strip (under lighting conditions that exceeded the “boundary conditions” of light intensity i.e., darkness or brightness, the application blocks the user from taking a picture). The results of this testing support that the device is not impacted by different light intensities.
4. Distance and Angle
Testing was conducted with 16 representative smart phones of different models and operating systems. Each phone was tested under “boundary conditions” that were 2 different distance conditions and 2 different angle conditions. The distance conditions were the longest distance from the color board and the shortest distance from the color board at which the device allowed the phone to take a picture of the strip and color board (at longer or shorter distances, the device blocks the user from taking a picture). The angle conditions were the most acute and most obtuse angles at which the device allowed the phone to take a picture of the urine test strip and color board (at more acute or obtuse angles, the device blocks the user from taking a picture). The performance of the device was not impacted under these “boundary conditions”.
5. Shadow
Testing was conducted with 16 representative smart phones of different models and operating systems under different shadow configurations of different intensity and covering different portions of the color-board and urine test strip. Six different shadow configurations and 2 different shadow intensities were tested. For 3 of the shadow configurations, the device blocked the user from taking a picture of the color-board and urine test strip. For the other 3 shadow configurations, the device performance was not impacted by the presence of shadows on the color-board and test strip.
6. Blurring
Testing was conducted with 16 representative smart phones of different models and operating systems under 14 different conditions of blurred images consisting of different levels of focus and motion blur. Under conditions that the devices detected too much image blur, the user was blocked from taking a picture of the color-board and the urine test strip. Under conditions where the device allowed a picture of the color-board and urine test strip to be taken, the device performance was not impacted by image blur.
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7. Misplaced Urine Stick
Testing was conducted with 16 representative smart phones of different models and operating systems with 8 different urine test strip placements. Of the 8 different placements, 4 urine test strip placements were recognized as invalid by the device and the device blocked the user from taking a picture of the color-board and urine test strip. When the device determined the stick placement to be valid, variations in stick placement did not impact the performance of the device.
8. Dirty Color-Board
Testing was conducted with 16 representative smart phones of different models and operating systems. Testing was conducted with 3 substances (urine, coffee, and ink) and 3 different "dirty" configurations covering different sections of the color-board and urine test strip. The device blocked the user from taking a picture of the color-board and urine test strip under "dirty" configurations that the device determined to be invalid. Under the "dirty" conditions the device determined to be valid, the performance of the device was not impacted.
9. Operating Conditions
Testing was conducted at four different operating conditions: 95% relative humidity (RH) at 35°C, 95% RH at 10°C, 10% RH at 35°C, and 10% RH at 10°C. Testing was conducted using two representative smart phones of different models. The performance of the device was not impacted under the conditions tested.
VIII Proposed Labeling:
The labeling supports the finding of substantial equivalence for this device.
IX Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
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Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.