The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay is for the semi-quantitative determination of autoantibodies to Zinc Transporter 8 (ZnT8) in human serum. The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay may be useful as an aid in the diagnosis of Type 1 diabetes mellitus (autoimmune mediated diabetes). The ZnT8Ab assay is not to be used alone and is to be used in conjunction with other clinical and laboratory findings.
Device Story
The KRONUS ZnT8Ab ELISA is an in vitro diagnostic assay used by laboratory professionals in clinical settings. It detects autoantibodies to Zinc Transporter 8 (ZnT8) in human serum samples using immunochemical techniques. The assay provides semi-quantitative results that assist clinicians in the diagnosis of Type 1 diabetes mellitus. Because the test is not a stand-alone diagnostic tool, results must be interpreted alongside clinical history, physical examination, and other laboratory tests (e.g., pancreatic or insulin autoantibody tests). The device is intended to support clinical decision-making; however, it is not indicated for monitoring disease stage or treatment response. The absence of ZnT8 autoantibodies does not rule out a diagnosis of Type 1 diabetes.
Clinical Evidence
Clinical performance must be established by comparing device results against a clinical diagnostic standard for Type 1 diabetes mellitus. Studies must include representative samples from all age strata, including subjects under 18 years old. Differential diagnosis groups must include Type 2 diabetes, metabolic syndrome, latent autoimmune diabetes in adults, other autoimmune diseases (e.g., celiac, SLE, rheumatoid arthritis, Hashimoto’s), infection, renal disease, and testicular cancer. Data must demonstrate clinical sensitivity and specificity in a tabular format.
Technological Characteristics
Immunochemical ELISA assay for semi-quantitative detection of ZnT8 autoantibodies in human serum. Includes kit components, ancillary reagents, and instrumentation. Requires internal and external quality controls. Performance characteristics include precision, linearity, analytical sensitivity (LoB, LoD, LoQ), analytical specificity (interference and cross-reactivity), and stability (real-time, specimen).
Indications for Use
Indicated for the semi-quantitative determination of ZnT8 autoantibodies in human serum to aid in the diagnosis of Type 1 diabetes mellitus. For use by laboratory professionals in a clinical setting. Not for use as a stand-alone diagnostic test.
Regulatory Classification
Identification
A zinc transporter 8 autoantibody immunological test system is a device that consists of reagents used to measure, by immunochemical techniques, the autoantibodies in human serum samples that react with Zinc Transporter 8 (ZnT8). The measurements aid in the diagnosis of Type 1 diabetes mellitus (autoimmune mediated diabetes) in conjunction with other clinical and laboratory findings.
Special Controls
Zinc Transporter 8 Autoantibody immunological test system must comply with the following special controls: 1) Premarket notification submissions must include the following information: A detailed description of the device that includes: A) A detailed description of all components in the test system, including a description of the assay components in the kit and all required ancillary reagents. B) A detailed description of instrumentation and equipment, and illustrations or photographs of non-standard equipment or methods if applicable. C) Detailed documentation of the device software, including, but not limited to, standalone software applications and hardware-based devices that incorporate software where applicable. D) A detailed description of appropriate internal and external quality controls that are recommended or provided. The description must identify those control elements that are incorporated into the recommended testing procedures. E) Detailed specifications for sample collection, processing and storage. F) A detailed description of methodology and assay procedure. G) Detailed specification of the criteria for test results interpretation and reporting. Information that demonstrates the performance characteristics of the device, including: A) Device precision/reproducibility data generated from within-run, between-run, between-day, between-lot, between-operator, betweeninstruments, between-site, and total precision for multiple nonconsecutive days as applicable. A well characterized panel of patient samples or pools from the intended use population that covers the device measuring range must be used. B) Device linearity data generated from patient samples covering the assay measuring range if applicable. C') Information on traceability to a reference material and description of value assignment of calibrators and controls if applicable. D) Device analytical sensitivity data, including limit of blank, limit of detection and limit of quantitation if applicable. E) Device analytical specificity data, including interference by endogenous and exogenous substances, as well as cross-reactivity with samples derived from patients with other autoimmune diseases or conditions. F) Device instrument carryover data when applicable. G) Device stability data including real-time stability under various storage times and temperatures. H) Specimen stability data, including stability under various storage times, temperatures, freeze-thaw and transport conditions where appropriate. I) Method comparison data generated by comparison of the results obtained with the device to those obtained with a legally marketed predicate device with similar indication of use. Patient samples from the intended use population covering the device measuring range must be used. J) Specimen matrix comparison data if more than one specimen type or anticoagulant can be tested with the device. Samples used for comparison must be from patient samples covering the device measuring range. K) A description of how the assay cut-off (the medical decision point between positive and negative) was established and validated as well as supporting data. L) Clinical performance must be established by comparing data generated by testing samples from the intended use population and the differential diagnosis groups with the device to the clinical diagnostic standard. M) Expected/ reference values generated by testing an adequate number of samples from apparently healthy normal individuals. Identification of risk mitigation elements used by the device, including description of all additional procedures, methods, and practices incorporated into the directions for use that mitigate risks associated with testing. 2) Your 21 CFR 809.10(a) compliant label and 21 CFR 809.10(b) compliant labeling must include warnings relevant to the assay including: i. A warning statement that reads "The device is for use by laboratory professionals in a clinical laboratory setting." ii. A warning statement that reads "The test is not a stand-alone test but an adjunct to other clinical information. A diagnosis of Type 1 diabetes mellitus should not be made on a single test result. The clinical symptoms, results on physical examination, and laboratory tests (e.g., serological tests), when appropriate, should always be taken into account when considering the diagnosis of Type 1 diabetes mellitus and Type 2 diabetes mellitus." iii. A warning statement that reads "Absence of Zinc T8 autoantibody does not rule out a diagnosis of Type 1 diabetes mellitus." iv. A warning statement that reads "The assay has not been demonstrated to be effective for monitoring the stage of disease or its response to treatment." 3) Your 21 CFR 809.10(b) compliant labeling must include a description of the protocol and performance studies performed in accordance with special control (1)(ii) and a summary of the results.
*Classification.* Class II (special controls). The special controls for this device are:(1) Premarket notification submissions must include the following information:
(i) A detailed description of the device that includes:
(A) A detailed description of all components in the test system, including a description of the assay components in the kit and all required ancillary reagents;
(B) A detailed description of instrumentation and equipment, and illustrations or photographs of non-standard equipment or methods if applicable;
(C) Detailed documentation of the device software, including, but not limited to, standalone software applications and hardware-based devices that incorporate software where applicable;
(D) A detailed description of appropriate internal and external quality controls that are recommended or provided. The description must identify those control elements that are incorporated into the recommended testing procedures;
(E) Detailed specifications for sample collection, processing, and storage;
(F) A detailed description of methodology and assay procedure; and
(G) Detailed specification of the criteria for test results interpretation and reporting.
(ii) Information that demonstrates the performance characteristics of the device, including:
(A) Device precision/reproducibility data generated from within-run, between-run, between-day, between-lot, between-operator, between-instruments, between-site, and total precision for multiple nonconsecutive days as applicable. A well characterized panel of patient samples or pools from the intended use population that covers the device measuring range must be used;
(B) Device linearity data generated from patient samples covering the assay measuring range if applicable;
(C) Information on traceability to a reference material and description of value assignment of calibrators and controls if applicable;
(D) Device analytical sensitivity data, including limit of blank, limit of detection and limit of quantitation if applicable;
(E) Device analytical specificity data, including interference by endogenous and exogenous substances, as well as cross-reactivity with samples derived from patients with other autoimmune diseases or conditions;
(F) Device instrument carryover data when applicable;
(G) Device stability data including real-time stability under various storage times and temperatures;
(H) Specimen stability data, including stability under various storage times, temperatures, freeze-thaw, and transport conditions where appropriate;
(I) Method comparison data generated by comparison of the results obtained with the device to those obtained with a legally marketed predicate device with similar indication of use. Patient samples from the intended use population covering the device measuring range must be used;
(J) Specimen matrix comparison data if more than one specimen type or anticoagulant can be tested with the device. Samples used for comparison must be from patient samples covering the device measuring range;
(K) A description of how the assay cut-off (the medical decision point between positive and negative) was established and validated as well as supporting data;
(L) Clinical performance must be established by comparing data generated by testing samples from the intended use population and the differential diagnosis groups with the device to the clinical diagnostic standard. The diagnosis of Type 1 diabetes mellitus must be based on clinical history, physical examination, and laboratory tests, such as one or more pancreatic or insulin autoantibody test. Because the intended use population for Type 1 diabetes mellitus includes subjects less than 18 years old, samples from representative numbers of these subjects must be included. Representative numbers of samples from all age strata must also be included. The differential diagnosis groups must include, but not be limited to the following: Type 2 diabetes mellitus; metabolic syndrome; latent autoimmune diabetes in adults; other autoimmune diseases such as celiac disease (without a concomitant diagnosis of Type 1 diabetes mellitus), systemic lupus erythematosus, rheumatoid arthritis, and Hashimoto's thyroiditis; infection; renal disease; and testicular cancer. Diseases for the differential groups must be based on established diagnostic criteria and clinical evaluation. For all samples, the diagnostic clinical criteria and the demographic information must be collected and provided. The clinical validation results must demonstrate clinical sensitivity and clinical specificity for the test values based on the presence or absence of Type 1 diabetes mellitus. The data must be summarized in tabular format comparing the interpretation of results to the disease status; and
(M) Expected/reference values generated by testing an adequate number of samples from apparently healthy normal individuals.
(iii) Identification of risk mitigation elements used by the device, including description of all additional procedures, methods, and practices incorporated into the directions for use that mitigate risks associated with testing.
(2) Your 21 CFR 809.10(a) compliant label and 21 CFR 809.10(b) compliant labeling must include warnings relevant to the assay including:
(i) A warning statement that reads, “The device is for use by laboratory professionals in a clinical laboratory setting”;
(ii) A warning statement that reads, “The test is not a stand-alone test but an adjunct to other clinical information. A diagnosis of Type 1 diabetes mellitus should not be made on a single test result. The clinical symptoms, results on physical examination, and laboratory tests (
*e.g.,* serological tests), when appropriate, should always be taken into account when considering the diagnosis of Type 1 diabetes mellitus and Type 2 diabetes mellitus”;(iii) A warning statement that reads, “Absence of Zinc T8 autoantibody does not rule out a diagnosis of Type 1 diabetes mellitus”; and
(iv) A warning statement that reads, “The assay has not been demonstrated to be effective for monitoring the stage of disease or its response to treatment.”
(3) Your 21 CFR 809.10(b) compliant labeling must include a description of the protocol and performance studies performed in accordance with paragraph (b)(1)(ii) of this section and a summary of the results.
Submission Summary (Full Text)
{0}------------------------------------------------
# EVALUATION OF AUTOMATIC CLASS III DESIGNATION FOR KRONUS Zinc Transporter 8 Autoantibody ELISA Assay DECISION SUMMARY
## A. DEN:
DEN140001
#### B. Purpose for Submission:
De Novo request for evaluation of automatic class III designation for the KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay
#### C. Measurand:
Zinc Transporter 8 Autoantibody (ZnT8Ab)
#### D. Type of Test:
The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay is for the semiquantitative determination of autoantibodies to Zinc Transporter 8 (ZnT8) in human serum. The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay may be useful as an aid in the diagnosis of Type 1 diabetes mellitus (autoimmune mediated diabetes).
## E. Applicant:
KRONUS Market Development Associates, INC.
#### F. Proprietary and Established Names:
KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay
#### G. Regulatory Information:
- 1. Regulation section:
21 CFR § 866.5670
- 2. Classification:
Class II
- 3. Product code:
PHF
{1}------------------------------------------------
## 4. Panel:
82-Immunology
# H. Intended Use:
- 1. Intended use(s):
The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay is for the semi-quantitative determination of autoantibodies to Zinc Transporter 8 (ZnT8) in human serum. The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay may be useful as an aid in the diagnosis of Type 1 diabetes mellitus (autoimmune mediated diabetes). The ZnT8Ab assay is not to be used alone and is to be used in conjunction with other clinical and laboratory findings.
# 2. Indication(s) for use:
Same as Intended use.
- 3. Special conditions for use statement(s):
For prescription use only in accordance with 21 CFR 801.109.
- 4. Special instrument requirements:
ELISA Plate Reader suitable for 96-well format and capable of measuring at 450 nm, and ELISA plate shaker capable of 500 shakes/ minute.
# I. Device Description:
The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay contains the following: strip wells coated with ZnT8 (96 wells in total) and supplied as 12 strips of 8 wells in a frame and sealed in a foil bag with desiccant; ready-to-use 4 levels of calibrators (10, 20, 75, and 500 U/mL, 5x0.7 mL each); one each ready-to-use positive I, positive II and negative control serum (1x0.7 mL); Zinc T8 Biotin (lyophilized) 3x5.5 mL (reconstituted); ready-to-use reconstitution buffer for Zinc T8 Biotin 2x15 mL (colored red); Streptavidin Peroxidase (SA-POD dilute before use) 1x0.7 mL; ready-to-use diluent for SA-POD 1x15 mL; ready-to-use peroxidase substrate (TMB) 1x15 mL; concentrated wash solution (dilute with deionized water before use) 1x125 mL and ready-to-use stop solution 1x12 mL.
# J. Standard/Guidance Document Referenced (if applicable):
Not applicable
# K. Test Principle:
{2}------------------------------------------------
The KRONUS Zinc Transporter 8 Autoantibody (ZnT8Ab) ELISA Assay depends on the ability of ZnT8 autoantibodies to act divalently and form a bridge between ZnT8 coated on the ELISA plate wells and liquid phase ZnT8- biotin. The ZnT8-biotin bound is then quantitated by addition of streptavidin peroxidase and a colorgenic substrate (TMB) with reading of the final absorbances at 450 nm. The absorbance of each vial is directly proportional to the amount of antibody present. Calibrator values are plotted on linear graph paper and the antibody concentrations of the controls and patient specimens are interpolated from the curve.
#### L. Performance Characteristics (if/when applicable):
#### 1. Analytical performance:
- Precision/Reproducibility: a.
#### Intra-assay
The intra-assay precision was determined by testing nine serum specimens which included one close to the assay cut-off (15.4 U/mL); three low (6.9, 7.8, and 10.2 U/mL); one moderate (25.9 U/mL), and four high (66.3, 222.2, 441.5 and 471.5 U/mL). Twenty five (20-25) replicates of each sample were assayed in a single assay on a single day. Results showed %CVs ranged from 1.7-5.6% (see table below).
| Sample | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|-------------|-----|-----|------|------|------|------|-------|-------|-------|
| n | 20 | 20 | 20 | 25 | 25 | 20 | 20 | 20 | 20 |
| Mean (U/mL) | 6.9 | 7.8 | 10.2 | 15.4 | 25.9 | 66.3 | 222.2 | 441.5 | 471.4 |
| SD (U/mL) | 0.2 | 0.4 | 0.4 | 0.5 | 1.2 | 1.7 | 11.8 | 7.6 | 13.5 |
| % CV | 3.3 | 5.6 | 4.2 | 3.3 | 4.5 | 2.5 | 5.3 | 1.7 | 2.9 |
#### Inter-assay
The inter-assay precision was determined by testing eleven samples: five serum specimens once a day for twenty days, two serum specimens once a day for 18 days and four sera for once a day for 10 days. The serum specimens consisted of two specimens with anti-ZnT8Ab concentration of 16.1 and 16.3 U/mL close to the assay 15 U/mL cut-off; four low levels (5.8, 7.2, 10.9 and 14.2 U/mL); one moderate level (28.7 U/mL) and three high levels (73.7, 250.3. 446.5 and 465.1 U/mL). The %CVs ranged from 2.9-17.7% (see table below).
| Sample | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
|-------------|------|------|------|------|------|------|-------|------|------|-------|-------|
| n | 18 | 18 | 10 | 10 | 20 | 10 | 10 | 20 | 20 | 20 | 20 |
| Mean (U/mL) | 5.8 | 7.2 | 10.9 | 16.1 | 28.7 | 73.7 | 250.3 | 14.2 | 16.3 | 446.5 | 465.1 |
| SD (U/mL) | 0.9 | 0.9 | 0.8 | 1.6 | 2.9 | 3.4 | 44.2 | 0.5 | 0.5 | 14.7 | 16.9 |
| % CV | 16.0 | 12.3 | 7.6 | 9.8 | 10.2 | 4.7 | 17.7 | 3.5 | 2.9 | 3.3 | 3.6 |
Lot-to-lot reproducibility:
{3}------------------------------------------------
Ten kit lots were tested using two control samples (48.4 and 156.3 U/mL) over a period of 96 weeks. The %CV for lot-to-lot reproducibility ranged from 7.6-9.2%.
#### Lab to Lab reproducibility:
Thirty-five samples (ranging from 0 to 1299 U/mL) and kit controls were assayed at two different laboratories. The correlation between laboratories was R = 0.984 (y = 0.9199x +0.3183).
- b. Linearity/assay reportable range:
Three positive samples were diluted (10 dilutions ranged from neat to 1:500). The observed values were graphed against the calculated values and a linear regression was performed. Results are summarized below:
| Sample | Dilution range<br>(U/mL) | Slope<br>(95%CI) | Y - Intercept<br>(95% CI) | R2 |
|--------|--------------------------|------------------|---------------------------|--------|
| A | 75.4 - 485.3 | 0.9539 | -59.55 | 0.9499 |
| B | 7.0 - 57.8 | 0.9556 | -0.5562 | 0.9783 |
The assay is linear for concentrations of 7.0 to 485 U/mL. The Package Insert Calculation Section states: "For samples that result in values greater than the 500 U/mL (greater than the highest calibrator) KRONUS recommends reporting the value as "greater than 500 U/mL"
#### High dose hook effect:
No hook effect was observed for ZnT8Ab concentration up to estimated 1980 U/mL.
- Traceability, Stability, Expected values (controls, calibrators, or methods): C.
There is no recognized reference standard available. The ZnT8 calibrator and controls (positive and negative) are prepared in-house and arbitrary units are assigned during the development process.
#### Stability
A real-time stability study was performed on three lots of ZnT8 Ab ELISA kit using 2 positive controls, a negative control and 11 samples (5 positive and 6 negative samples). Data support a shelf life of 9 months.
- d. Detection limit:
The limit of blank (LoB) was determined by sequentially testing the negative control included with the kit sixty (60) times. A calibration curve of absorbance450mm VS. concentration was constructed. The mean and SD for the absorbance450mm of the negative control were calculated and the mean + 2 SDs was read off the calibration curve to give a U/mL value. The LoB was computed to be 2.1 U/mL.
{4}------------------------------------------------
The limit of detection (LoD) was determined by sequentially testing twenty five (25) replicates each of four healthy blood donor samples for a total of 100 samples. The LoD determination used a non-parametric statistical calculation. The 95th percentile corresponds to the 95.5 ordered observation of results placed in ascending order which yields a LoD estimate of 5.6 U/mL.
- e. Analytical specificity:
#### Endogenous Interference
No significant interference was observed in 10 specimens (with ZnT8Ab levels ranging from 2.1 - 356 U/mL) spiked with hemoglobin (at 500 mg/dL), bilirubin (at 20 mg/dL) and Intralipids (at 1000 and 3000 mg/dL). The Package Insert 'Specimen Collection and Handling Section' states: "Sera should be clear and grossly lipemic or hemolyzed samples should not be used".
#### Cross-reactivity:
The KRONUS ZnT8Ab ELISA Assay Kit was tested with 246 sera from other autoimmune diseases and conditions. These samples comprised of 24 Graves' Disease, 9 Myasthenia gravis, 26 Rheumatoid arthritis, 23 Addison Disease, 3 Neuromyelitis optica, 24 Hashimoto's Disease; 60 Type 2 Diabetes mellitus; 10 Celiac Disease; 9 Systemic Lupus Erythematosus; 6 Testicular Cancer; 37 Metabolic syndrome; 10 Kidney Disease and 5 Urinary Tract Infection.
Two hundred forty one (241) of 246 specimens were negative with the KRONUS ZnT8Ab ELISA Assay Kit. The five positive sera were as follows: 1 Graves' Disease at 15.6 U/mL; 2 Addison Disease at 48.1 U/mL and 23.5 U/mL; 1 Type 2 Diabetes at >500 U/mL and 1 Kidney Disease at 65 U/mL.
| Patient Group | No. of Samples Positive for<br>ZnT8Ab | % |
|------------------------------|---------------------------------------|----|
| Graves' Disease | 1/24 | 4 |
| Hashimoto's Thyroiditis | 0/24 | 0 |
| Addison's Disease | 2/23 | 9 |
| Myasthenia Gravis | 0/9 | 0 |
| Neuromyelitis Optica | 0/3 | 0 |
| Type 2 Diabetes | 1/60 | 2 |
| Rheumatoid Arthritis | 0/26 | 0 |
| Celiac Disease | 0/10 | 0 |
| Systemic Lupus Erythematosus | 0/9 | 0 |
| Testicular Cancer | 0/6 | 0 |
| Metabolic Syndrome | 0/37 | 0 |
| Kidney Disease | 1/10 | 10 |
| Urinary Tract Infection | 0/5 | 0 |
{5}------------------------------------------------
#### f. Assay cut-off:
The assay cut-off (greater than or equal to 15 U/mL is positive) for the KRONUS ZnT8Ab Assay Kit was determined by testing specimens from 397 US healthy blood donors (291 Black and 6 Caucasian males as well as 98 Black, 1 Hispanic and 1 Asian females). Ninety-nine percent (394/397) were negative for ZnT8Ab. The ZnT8Ab concentrations in the three positive samples were 19, 41 and 45 U/mL. The mean result was 1.90 U/mL with a SD of 3.84.
#### 2. Comparison studies:
- a. Method comparison with predicate device:
Refer to Clinical studies.
- b. Matrix comparison:
Not applicable
- 3. Clinical studies:
- Clinical Sensitivity and Specificity: a.
The clinical performance was evaluated on 569 clinically defined patient samples. These samples had the following diagnosis: 323 patients with Type 1 diabetes mellitus ("T1D" or "T1 DM"), 60 Type 2 diabetes mellitus ("T2 DM") and 186 other diseases (24 Graves' Disease, 9 Myasthenia Gravis, 26 Rheumatoid Arthritis, 23 Addison's Disease, 3 Neuromyelitis Optica, 24 Hashimoto's Disease; 10 Celiac Disease; 9 Systemic Lupus Erythematosus; 6 Testicular Cancer; 37 Metabolic syndrome; 10 Kidney Disease and 5 Urinary Tract Infection). The clinical sensitivity, specificity and overall agreement are summarized below:
| | Diagnosis | | | |
|------------------------------|-----------|-------------------|-----------------------------------|--------|
| | | Positive<br>(TID) | Negative<br>(Non-Target Diseases) | Totals |
| ZnT8Ab<br>ELISA<br>Assay Kit | Positive | 220 | 5 | 225 |
| | Negative | 103 | 241 | 344 |
| | Total | 323 | 246 | 569 |
Sensitivity: 68 % (220/323) (95% C.I.: 63-73%) 98 % (241/246) (95% C.I.: 95-99%) Specificity: Overall Agreement: 81% (461/569) (95% C.I.: 76-85 %)
The rate of positivity was found to decrease with increasing age for the T1D population. Positivity rates based on age strata in the T1D population is shown below.
{6}------------------------------------------------
| Age | n | # Positive | Positive (%) | Negative (%) |
|-------|-----|------------|--------------|--------------|
| 11-20 | 215 | 166 | 77 | 23 |
| 21-25 | 27 | 18 | 67 | 33 |
| 26-37 | 73 | 33 | 45 | 55 |
| 38+ | 8 | 3 | 38 | 62 |
| Total | 323 | 220 | 68 | 32 |
- c. Other clinical supportive data (when a. and b. are not applicable): Not applicable.
- 4. Clinical cut-off:
Refer to assay cut-off.
- 5. Expected values/Reference range:
The expected value from 394 of the total 397 healthy individual blood donors was <15 U/mL (3 donors had >15 U/mL values).
# M. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 801, 21 CFR Part 809, 21 CFR 801.109, and the special controls.
# N. Identified Risks and Required Mitigations:
| Identified Risks | Required Mitigations |
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------|
| Inaccurate test results that provide false positive or false negative results can lead to improper patient management. | Special controls (1), (2), and (3) |
| Failure to correctly interpret test results can lead to false positive or false negative results | Special controls (1) (iii), (2), and (3) |
{7}------------------------------------------------
#### O. Benefit/Risk Analysis:
| Summary | |
|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Summary of<br>the Benefit(s) | Patients with Type 1 diabetes mellitus (“T1D” or “T1DM”) often have antibodies to<br>pancreatic islet cell antigens. This assay represents the first to target antibodies to the<br>zinc transporter, expressed in pancreatic islet cells. The assay can help in the diagnosis<br>of T1D patients. In the clinical study, the assay demonstrated a clinical sensitivity of<br>68% and specificity of 98%. The study identified 11 of 323 T1D patients (3.4%) who<br>were positive only for ZnT8Ab, and negative for other existing pancreatic<br>autoantibodies, such as insulin antibodies (IAA), insulinoma-associated protein 2<br>autoantibodies (IA-2A), and glutamic acid decarboxylase autoantibodies (GADA).<br>This highlights the clinical utility of adding ZnT8 to the existing islet cell<br>autoantibodies to increase the capture of patients who potentially have T1D. |
| Summary of<br>the Risk(s) | The risks are related to the consequences of decisions made based on false negative<br>and false positive results due to inaccurate test results, or failure to correctly<br>interpret test results. The combination of general and special controls would<br>mitigate these risks. A false negative result could lead to a missed or delayed<br>diagnosis of T1D, and a false positive result could lead to additional, unnecessary<br>evaluation and testing. The false negative risk of 32% found in the clinical study is<br>sufficiently mitigated by language in the Intended Use statement in the package<br>insert (labeling) that the assay is not to be used alone and is to be used in<br>conjunction with other clinical and laboratory findings. The false positive risk of<br>2% is extremely low. |
| Conclusions<br>Do the<br>probable<br>benefits<br>outweigh the<br>probable risks? | The probable benefit of aiding in the increased detection of T1D patients<br>outweighs the probable risk of a false negative assay result in 32% of patients with<br>T1D and a false positive result in 2% of patients without T1D. The combination of<br>general controls and special controls, including product labeling (package insert),<br>adequately mitigates the risks posed by use of the assay.<br><br>The addition of ZnT8Ab to the existing islet cell autoantibodies increases the<br>capture of patients who potentially have T1D and outweighs risks of inaccurate test<br>results, which are adequately described and sufficiently mitigated by statements in<br>the Intended Use and Limitations sections of the package insert (product labeling). |
## P. Conclusion:
The information provided in this de novo submission is sufficient to classify this device into class II under regulation 21 CFR 866.5670 with special controls. FDA believes that special controls, along with the applicable general controls, provide reasonable assurance of the safety and effectiveness of the device type. The device is classified under the following:
Product Code: PHF Zinc Transporter 8 Autoantibody immunological test system Device Type:
{8}------------------------------------------------
Class: II (special controls) Regulation: 21 CFR 866.5670
i.
Identification. A Zinc Transporter 8 Autoantibody immunological test system is a device that consists of reagents used to measure, by immunochemical techniques, the autoantibodies in human serum samples that react with Zinc Transporter 8 (ZnT8). The measurements aid in the diagnosis of Type 1 diabetes mellitus (autoimmune mediated diabetes) in conjunction with other clinical and laboratory findings.
- Classification. Class II (special controls). Zinc Transporter 8 Autoantibody immunological (a) test system must comply with the following special controls:
- 1) Premarket notification submissions must include the following information:
- A detailed description of the device that includes:
- A ) A detailed description of all components in the test system, including a description of the assay components in the kit and all required ancillary reagents.
- B) A detailed description of instrumentation and equipment, and illustrations or photographs of non-standard equipment or methods if applicable.
- C) Detailed documentation of the device software, including, but not limited to, standalone software applications and hardware-based devices that incorporate software where applicable.
- D) A detailed description of appropriate internal and external quality controls that are recommended or provided. The description must identify those control elements that are incorporated into the recommended testing procedures.
- E) Detailed specifications for sample collection, processing and storage.
- F) A detailed description of methodology and assay procedure.
- G) Detailed specification of the criteria for test results interpretation and reporting.
- Information that demonstrates the performance characteristics of the ii. device, including:
- A) Device precision/reproducibility data generated from within-run, between-run, between-day, between-lot, between-operator, betweeninstruments, between-site, and total precision for multiple nonconsecutive days as applicable. A well characterized panel of patient samples or pools from the intended use population that covers the device measuring range must be used.
- B) Device linearity data generated from patient samples covering the assay measuring range if applicable.
- C') Information on traceability to a reference material and description of value assignment of calibrators and controls if applicable.
- D) Device analytical sensitivity data, including limit of blank, limit of detection and limit of quantitation if applicable.
{9}------------------------------------------------
- E) Device analytical specificity data, including interference by endogenous and exogenous substances, as well as cross-reactivity with samples derived from patients with other autoimmune diseases or conditions.
- F) Device instrument carryover data when applicable.
- G) Device stability data including real-time stability under various storage times and temperatures.
- H) Specimen stability data, including stability under various storage times, temperatures, freeze-thaw and transport conditions where appropriate.
- I) Method comparison data generated by comparison of the results obtained with the device to those obtained with a legally marketed predicate device with similar indication of use. Patient samples from the intended use population covering the device measuring range must be used.
- J) Specimen matrix comparison data if more than one specimen type or anticoagulant can be tested with the device. Samples used for comparison must be from patient samples covering the device measuring range.
- K ) A description of how the assay cut-off (the medical decision point between positive and negative) was established and validated as well as supporting data.
- L) Clinical performance must be established by comparing data generated by testing samples from the intended use population and the differential diagnosis groups with the device to the clinical diagnostic standard. The diagnosis of Type 1 diabetes mellitus must be based on clinical history, physical examination, and laboratory tests, such as one or more pancreatic or insulin autoantibody test. Because the intended use population for Type 1 diabetes mellitus includes subjects less than 18 years old, samples from representative numbers of these subjects must be included. Representative numbers of samples from all age strata must be also be included. The differential diagnosis groups must include, but not be limited to, the following: Type 2 diabetes mellitus; metabolic syndrome; latent autoimmune diabetes in adults; other autoimmune diseases such as celiac disease (without a concomitant diagnosis of Type 1 diabetes mellitus), systemic lupus erythematosus, rheumatoid arthritis, and Hashimoto's thyroiditis; infection; renal disease; and testicular cancer. Diseases for the differential groups must be based on established diagnostic criteria and clinical evaluation. For all samples, the diagnostic clinical criteria and the demographic information must be collected and provided. The clinical validation results must demonstrate clinical sensitivity and clinical specificity for the test values based on the presence or absence of Type 1 diabetes mellitus. The data must be summarized in tabular format comparing the interpretation of results to the disease status.
{10}------------------------------------------------
- M) Expected/ reference values generated by testing an adequate number of samples from apparently healthy normal individuals.
- Identification of risk mitigation elements used by the device, including iii description of all additional procedures, methods, and practices incorporated into the directions for use that mitigate risks associated with testing.
- 2) Your 21 CFR 809.10(a) compliant label and 21 CFR 809.10(b) compliant labeling must include warnings relevant to the assay including:
- i. A warning statement that reads "The device is for use by laboratory professionals in a clinical laboratory setting."
- ii. A warning statement that reads "The test is not a stand-alone test but an adjunct to other clinical information. A diagnosis of Type 1 diabetes mellitus should not be made on a single test result. The clinical symptoms, results on physical examination, and laboratory tests (e.g., serological tests), when appropriate, should always be taken into account when considering the diagnosis of Type 1 diabetes mellitus and Type 2 diabetes mellitus."
- A warning statement that reads "Absence of Zinc T8 autoantibody does not rule iii. out a diagnosis of Type 1 diabetes mellitus."
- iv. A warning statement that reads "The assay has not been demonstrated to be effective for monitoring the stage of disease or its response to treatment."
- 3) Your 21 CFR 809.10(b) compliant labeling must include a description of the protocol and performance studies performed in accordance with special control (1)(ii) and a summary of the results.
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
Learn the FDA Browser
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.