FORA G30 BLOOD GLUCOSE MONITORING SYSTEM, MODEL TD-4241
Applicant
Taidoc Technology Corporation
Product Code
NBW · Clinical Chemistry
Decision Date
May 12, 2009
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1345
Device Class
Class 2
Attributes
Pediatric
Indications for Use
The FORA G30 Blood glucose monitoring system is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and the following alternative sites: the palm, the forearm, the upper-arm, the calf and the thigh. It is intended for use by healthcare professionals and people with diabetes mellitus at home as an aid in monitoring the effectiveness of diabetes control program. It is not intended for the diagnosis of or screening for diabetes mellitus, and is not intended for use on neonates. The alternative site testing in the FORA G30 Blood glucose monitoring system can be used only during steady-state blood glucose conditions.
Device Story
FORA G30 Blood Glucose Monitoring System; uses electrochemical amperometric assay with glucose oxidase enzyme; inputs fresh capillary whole blood from finger or alternative sites (palm, forearm, upper-arm, calf, thigh); meter measures current produced by glucose oxidation; provides quantitative glucose concentration readout; used by healthcare professionals and patients at home; aids in monitoring diabetes control; includes automatic temperature compensation via thermistor; results displayed on LCD; memory stores 450 measurements; auto-shutoff after 3 minutes; powered by CR2032 battery.
Clinical Evidence
Performance evaluated in laboratory and clinical settings by healthcare professionals and lay users. Studies demonstrated satisfactory performance meeting intended use requirements.
Technological Characteristics
Electrochemical meter with dry reagent biosensor test strips. Quantitative measurement of glucose in fresh whole blood. Class II device (21 CFR 862.1345).
Indications for Use
Indicated for quantitative glucose measurement in fresh capillary whole blood from finger, palm, forearm, upper-arm, calf, and thigh. For use by healthcare professionals and people with diabetes mellitus as an aid in monitoring diabetes control programs. Not for diagnosis or screening of diabetes; not for use on neonates. Alternative site testing restricted to steady-state blood glucose conditions.
Regulatory Classification
Identification
A glucose test system is a device intended to measure glucose quantitatively in blood and other body fluids. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.
Special Controls
*Classification.* Class II (special controls). The device, when it is solely intended for use as a drink to test glucose tolerance, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.
Predicate Devices
Clever Chek TD-4230 blood glucose monitoring system (K070472)
Submission Summary (Full Text)
{0}
1
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number:
k090187
B. Purpose for Submission:
Clearance of a new device
C. Measurand:
Whole blood glucose
D. Type of Test:
Whole blood glucose concentration through a quantitative amperometric assay (Glucose Oxidase)
E. Applicant:
Taidoc Technology Corporation
F. Proprietary and Established Names:
FORA G30 Blood Glucose Monitoring System
G. Regulatory Information:
1. Regulation section:
21 CFR § 862.1345, Blood Glucose Test System
2. Classification:
Class II
3. Product code:
NBW, CGA
4. Panel:
75 (Clinical Chemistry)
H. Intended Use:
1. Intended use(s):
See indications for use below.
2. Indication(s) for use:
The FORA G30 Blood glucose monitoring system is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and the following alternative sites: the palm, the forearm, the upper-arm, the calf and the thigh. It is intended for use by healthcare professionals and people with diabetes mellitus at home as an aid in monitoring the effectiveness of diabetes control program. It is not intended for
{1}
the diagnosis of or screening for diabetes mellitus, and is not intended for use on neonates.
The alternative site testing in the FORA G30 Blood glucose monitoring system can be used only during steady-state blood glucose conditions.
3. Special conditions for use statement(s):
- Not intended for diagnosis of diabetes mellitus
- Not intended for use on neonates
- For in vitro diagnostic use only
- Not for use on critically ill patients, dehydrated patients or hyperosmolar patients
4. Special instrument requirements:
FORA G30 Blood Glucose Monitoring System
I. Device Description:
The FORA G30 Blood Glucose Monitoring System consists of a meter and test strips. The system utilizes an electrochemical method-based meter and dry reagent biosensor (test strips) for blood glucose testing, using the glucose oxidase enzyme. Control solutions were previously cleared under k041107.
J. Substantial Equivalence Information:
1. Predicate device name(s):
Clever Chek TD-4230 Blood Glucose Monitoring System
2. Predicate 510(k) number(s):
k070472
3. Comparison with predicate:
| Similarities | | |
| --- | --- | --- |
| Item | Predicate Device | Candidate Device |
| Intended Use | The Clever Chek TD-4230 Blood Glucose Monitoring System is intended for use in the quantitative measurement of glucose in whole blood taken from the finger, the palm, the forearm, the upper arm, the calf, and the thigh. They are intended for use by healthcare professionals and people with diabetes mellitus at home as an aid in monitoring the effectiveness of diabetes control program. They are not intended for the diagnosis of or screening for diabetes mellitus, and are not intended for use on neonates. | The FORA G30 Blood glucose monitoring system is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and the following alternative sites: the palm, the forearm, the upper-arm, the calf and the thigh. It is intended for use by healthcare professionals and people with diabetes mellitus at home as an aid in monitoring the effectiveness of diabetes control program. It is not intended for the diagnosis of or screening for diabetes mellitus, and is not intended for use on |
{2}
| Similarities | | |
| --- | --- | --- |
| Item | Predicate Device | Candidate Device |
| | | neonates. The alternative site testing in the FORA G30 Blood glucose monitoring system can be used only during steady-state blood glucose conditions. |
| Detection Method | Amperometry: measuring a current produced by a chemical reaction | Amperometry: measuring a current produced by a chemical reaction |
| Enzyme | Glucose Oxidase | Glucose Oxidase |
| Temperature Compensation | Automatic compensation with built-in thermister | Automatic compensation with built-in thermister |
| Measurement Range | 20 – 600 mg/dL | 20 – 600 mg/dL |
| Operating Condition | 10°C – 40°C, Below 85% R.H. | 10°C – 40°C, Below 85% R.H. |
| Strip Vial Opened Use Time | 90 days | 90 Days |
| Memory Feature | 450 measurements with day and time | 450 measurements with day and time |
| Auto Shut Off (min) | 3 | 3 |
| Alarm | Beeping sound and/or error message in LCD display | Beeping sound and/or error message in LCD display |
| Power | One CR2032 battery | One CR2032 battery |
| Differences | | |
| --- | --- | --- |
| Item | Predicate Device | Candidate Device |
| Meter Size (mm) | 94 x 20 x 48 | 85 x 52 x 15 |
| Weight (g) | 79.22 | 52.0 |
| Sample Volume (μL) | 0.7 | 0.5 |
| Reaction Time (sec) | 7 | 5 |
| Test Strip Calibration | Select code number from the meter | One code function |
| Test Strip Size (mm) | 33 (L) x 9 (W) x 0.72 (H) | 36 (L) x 8.5 (W) x 0.15 (H) |
| Test Strip Chemical Components | - Glucose oxidase (A. niger) 10%
- Electron shuttle 50%
- Enzyme protector 8%
- Non-reactive ingredients 32% | - Glucose oxidase (A. niger) 13%
- Electron shuttle 39%
- Enzyme protector 6%
- Non-reactive ingredients 42% |
{3}
| Differences | | |
| --- | --- | --- |
| Item | Predicate Device | Candidate Device |
| Appearance | | |
# K. Standard/Guidance Document Referenced (if applicable):
- ISO 15197 - In vitro diagnostic test systems - Requirements for blood glucose monitoring systems for self-testing in managing diabetes mellitus. Version - 2003(E). May 1, 2003.
- ISO 14971 - Medical devices - Application of risk management to medical devices, $1^{\text{st}}$ edition, 2000
- CLSI EP9-A - Method comparison and bias estimation using patient samples. Version - Vol.15, No.17. 1995.
- CLSI EP5-A - Evaluation of precision performance of clinical chemistry devices: Version - Vol.19, No.2. 1999.
- CLSI EP6-A - Evaluation of the linearity of quantitative analytical methods; proposed guideline - second edition
- CLSI EP7-A - Interference testing in clinical chemistry.
- Arch. Pathology Laboratory Medicine – Effects of different hematocrit levels on glucose measurements with handheld emters for point-of-care testing. Volume 124, August 2000
EN 13640:2002 - Stability testing of in vitro diagnostic medical devices
- IEC 61010-1:2001 - Safety requirements for electrical equipment for measurements, control, and laboratory use - part 1: general requirement
- IEC 60601-1:1988 - Medical Electrical Equipment - Part 1: General requirements for safety
# L. Test Principle:
The FORA G30 Blood Glucose Monitoring System uses electrochemical methodologies. The system quantitatively measures blood glucose level using an amperometric method, which involves detecting the current produced from glucose oxidation. The electrons generated during this reaction are transferred from the blood to the electrodes. The magnitude of the resultant current is proportional to the concentration of glucose in the specimen and the signal is converted into a readout displayed on the meter.
{4}
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
The sponsor’s precision studies were based on ISO 15197 and CLSI EP5-A recommendations. The within-run precision study samples used were venous blood (hematocrit range 38% - 54%) spiked with dextrose to create 5 levels of blood glucose. Three lots of test strips and 10 meters were used in the study, with 10 tests performed on each meter for a total of 100 tests per blood glucose level.
The results are as follows:
| Samples | No. of Tests | Average (mg/dL) | Standard Deviation (mg/dL) | Coefficient of Variation (%) |
| --- | --- | --- | --- | --- |
| Level 1 | 100 | 42.7 | 1.76 | 4.11 |
| Level 2 | 100 | 78.9 | 3.23 | 4.10 |
| Level 3 | 100 | 152.2 | 3.54 | 2.33 |
| Level 4 | 100 | 203.8 | 4.63 | 2.27 |
| Level 5 | 100 | 305.7 | 7.13 | 2.33 |
The day-to-day run precision study samples used were glucose control solutions. Low, medium, and high levels were used. Three lots of test strips and 10 meters were used in the study, with 1 test performed on each meter per day for 10 days, for a total of 100 tests per control level.
The results are as follows:
| Samples | No. of Tests | Average (mg/dL) | Standard Deviation (mg/dL) | Coefficient of Variation (%) |
| --- | --- | --- | --- | --- |
| Low Control | 300 | 82.7 | 2.51 | 3.04 |
| Medium Control | 300 | 145.1 | 3.09 | 2.13 |
| High Control | 300 | 334.9 | 5.40 | 1.61 |
b. Linearity/assay reportable range:
The sponsor indicated that the linearity study protocol was developed according to CLSI EP6-A. The candidate device was tested to verify linearity of the system using blood samples with glucose concentrations between 20-600 mg/dL. Venous blood samples were used. Samples were spiked with dextrose in order to create nine glucose levels (20, 40, 60, 90, 120, 200, 320, 420, 600 mg/dL). Testing was performed using the FORA G30 meter (candidate device) and the YSI-2300 glucose
{5}
analyzer (reference method). Two lots of test strips were used in the study with 5 tests per lot performed on each meter, for a total of 10 tests per blood glucose level.
The stated reportable range of the meter is 20-600 mg/dL
The results are as follows:
| Linear Regression | Correlation coefficient (R²) |
| --- | --- |
| y = 0.9819x + 1.9316 | 0.9997 |
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
The FORA G30 system (including meter and test strips) has an operating environment of 10 – 40°C and relative humidity below 85%. Performance testing supports this range. The system was also tested in extreme conditions to determine if it could operate correctly in its indicated range after being exposed to harsher conditions. Temperature exposure limits of the system were determined to be -20 – 60°C, and humidity exposure limits of 5 - 95% relative humidity. Drop tests and vibration tests were also performed on the device.
Test strips were examined using accelerated stability studies to determine unopened shelf life. The sponsor currently has real time stability testing to support unopened shelf life of the test strips for 12 months when stored between 4 – 40°C. In-use stability of the test strips is 90 days after the first opening.
In-use stability of the glucose control solution (cleared under k041107) is 90 days after the first opening when stored between 2 – 30°C.
d. Detection limit:
The measuring range of the system is 20 - 600 mg/dL. This range was verified by the linearity study (see section M.1.b.).
e. Analytical specificity:
Interference Study:
The sponsor indicated that the interference study protocol was developed according to CLSI EP7-A. Blood samples were collected in an anti-coagulant (Li-EDTA) vacuum tube from seven volunteers, and glucose levels were adjusted to a low (75-85 mg/dL) and a high (300 mg/dL) level using the YSI 2300 as a reference instrument. The percent bias caused by various interferences must be less than ± 10%. Interferents causing a bias greater than 10% are examined using a dose-response test to interpolate the concentration at which 10% bias would be observed.
The results are as follows:
{6}
| Exogenous substance | | | Concentration at which drug interference was observed | |
| --- | --- | --- | --- | --- |
| Therapeutic levels | | Maximum Test concentration | At low glucose level | At high glucose level |
| Acetaminophen (mg/dL) | 1-2 | 25 | 10 | 10 |
| Ascorbic acid (mg/dL) | 0.8-1.2 | 4 | 3 | 3 |
| Dopamine (mg/dL) | 0.4-1.6 | 6.25 | No interference up to test concentration | |
| L-Dopa (mg/dL) | 0.02-0.3 | 3 | No interference up to test concentration | 1.5 |
| Methyl Dopa (mg/dL) | 0.1-0.5 | 1.5 | 1.5 | 1.5 |
| Tolbutamide (mg/dL) | 5.3-10 | 64 | No interference up to test concentration | |
| Endogenous substance | | | Concentration at which drug interference was observed | |
| Physiological levels | | Maximum Test concentration | At low glucose level | At high glucose level |
| Uric acid (mg/dL) | 7 | 10 | 10 | 10 |
| Triglyceride (mg/dL) | 190 | 2000 | No interference up to test concentration | |
## Altitude Study:
An altitude study was performed on a mountain in Wuling, Taiwan with an elevation of 10,744 ft. The capillary blood glucose results of 20 volunteers were tested using the FORA G30 meter at high altitude and compared to the Roche Accu-Chek meter at high altitude. The results of this study are acceptable: 95% of the measurements must have a deviation less than 20% at ≥ 75 mg/dL and less than 15 mg/dL at < 75 mg/dL.
## Hematocrit Study:
To test accuracy due to the hematocrit effect, venous blood samples were collected in an anti-coagulant (Li-EDTA) vacuum tube, and glucose levels were adjusted to the following ranges; 40-60 mg/dL, 70-120 mg/dL, 120-200 mg/dL, 240-280 mg/dL, and 420-440 mg/dL and 480-520 mg/dL. Samples were then adjusted to hematocrit levels of 20%, 30%, 40%, 50%, and 60%. The YSI 2300 was used as the reference method.
The results of the hematocrit study were reviewed and found to be acceptable.
{7}
f. Assay cut-off: Not Applicable.
## 2. Comparison studies:
a. Method comparison with predicate device:
### Reference Method Comparison:
This study was performed in accordance with CLSI EP9-A and ISO 15197. Three clinical sites were used with 122 total patients (with samples ranging from 35 to 522 mg/dL). Samples below 40 mg/dL were obtained by allowing patient samples to glycolize, and then spiked to the appropriate level. Samples above 400 mg/dL were spiked. Health care professionals tested capillary whole blood using the FORA G30 (the candidate device) and the YSI 2300 (the reference method) and each site met the ISO 15197 standard where ninety-five percent (95%) of the individual glucose results shall fall within ±15 mg/dL of the results at glucose concentrations <75 mg/dL and within ±20% at glucose concentrations ≥75 mg/dL.
The results are as follows:
**Glucose Concentrations < 75 mg/dL:**
| Within ± 5 mg/dL | Within ± 10 mg/dL | Within ± 15 mg/dL |
| --- | --- | --- |
| 89% (16/18) | 100% (18/18) | 100% (18/18) |
**Glucose Concentrations ≥ 75 mg/dL:**
| Within ± 5% | Within ± 10% | Within ± 15% | Within ± 20% |
| --- | --- | --- | --- |
| 62% (64/104) | 94% (98/104) | 97% (101/104) | 99% (103/104) |
**Linear Regression Analysis:**
| Site# | Comparison | N | Slope and y-intercept | r |
| --- | --- | --- | --- | --- |
| 1 | FORA G30 vs. YSI-2300 | 41 | y = 1.007x + 0.570 | 0.990 |
| 2 | FORA G30 vs. YSI-2300 | 41 | y = 0.980x + 3.635 | 0.990 |
| 3 | FORA G30 vs. YSI-2300 | 40 | y = 1.000x + 2.740 | 0.993 |
| total | FORA G30 vs. YSI-2300 | 122 | y = 0.994x - 2.576 | 0.991 |
A Clarke error grid analysis was also presented; 99% (121/122) of results fall in zone A – clinically accurate. 1% (1/122) fall in zone B – deviating from the reference method by more than 20% but would lead to benign or no treatment.
**Lay-User Study:**
{8}
The study was performed in accordance with CLSI EP9-A and ISO 15197. 128 lay users at 3 different sites tested themselves once with the FORA G30 blood glucose meter. Lay users were given the user manual in English, and were given no additional instructions. Health care professionals then took one further measurement with the FORA G30 blood glucose meter, and the results between the lay users and health care professionals were compared.
The results are as follows:
Glucose Concentrations < 75 mg/dL:
| Within ± 5 mg/dL | Within ± 10 mg/dL | Within ± 15 mg/dL |
| --- | --- | --- |
| 54% (14/26) | 81% (21/26) | 100% (26/26) |
Glucose Concentrations ≥ 75 mg/dL:
| Within ± 5% | Within ± 10% | Within ± 15% | Within ± 20% |
| --- | --- | --- | --- |
| 47% (48/102) | 71% (72/102) | 86% (88/102) | 95% (97/102) |
Linear Regression Analysis:
| Site# | Comparison | N | Slope and y-intercept | r |
| --- | --- | --- | --- | --- |
| 1 | FORA G30 vs. YSI-2300 | 41 | y = 1.034x - 2.115 | 0.988 |
| 2 | FORA G30 vs. YSI-2300 | 42 | y = 1.027x - 3.809 | 0.974 |
| 3 | FORA G30 vs. YSI-2300 | 45 | y = 0.970x - 1.250 | 0.9621 |
| total | FORA G30 vs. YSI-2300 | 128 | y=1.001x - 1.503 | 0.972 |
A Clarke error grid analysis was also presented; 96% (123/128) of results fall in zone A – clinically accurate. 4% (5/128) fall in zone B – deviating from the reference method by more than 20% but would lead to benign or no treatment.
## Predicate Device Comparison:
This study was performed in accordance with CLSI EP9-A and ISO 15197. YSI 2300 was used as the reference method. Three clinical sites were used with 136 total patients (with samples ranging from 24 to 594 mg/dL). Samples < 40 mg/dL were obtained by allowing patient samples to glycolize, and are then spiked to the appropriate level. Samples > 400 mg/dL were spiked. Health care professionals tested capillary whole blood using the FORA G30 (the candidate device) and the Clever Chek TD-4230 (the predicate device) and each site met the ISO 15197 standard where ninety-five percent (95%) of the individual glucose results shall fall within ±15 mg/dL of the results at glucose concentrations < 75 mg/dL and within ±20% at glucose concentrations ≥75 mg/dL.
{9}
The results are as follows:
Glucose Concentrations < 75 mg/dL:
| | Within ± 5 mg/dL | Within ± 10 mg/dL | Within ± 15 mg/dL |
| --- | --- | --- | --- |
| FORA G30 | 89% (16/18) | 100% (18/18) | 100% (18/18) |
| Clever Chek TD-4230 | 94% (17/18) | 100% (18/18) | 100% (18/18) |
Glucose Concentrations ≥ 75 mg/dL:
| | Within ± 5% | Within ± 10% | Within ± 15% | Within ± 20% |
| --- | --- | --- | --- | --- |
| FORA G30 | 62% (64/104) | 94% (98/104) | 97% (101/104) | 99% (103/104) |
| Clever Chek TD-4230 | 61% (63/104) | 95% (99/104) | 98% (102/104) | 99% (103/104) |
Linear Regression Analysis:
| Comparison | N | Slope and y-intercept | r |
| --- | --- | --- | --- |
| FORA G30 vs. YSI-2300 | 122 | y = 0.994x - 2.576 | 0.991 |
| Clever Chek TD-4230 vs. YSI-2300 | 122 | y = 0.971x + 4.402 | 0.988 |
A Clarke error grid analysis was also presented; 99% (121/122) of results fall in zone A – clinically accurate. 1% (1/122) fall in zone B – deviating from the reference method by more than 20% but would lead to benign or no treatment. These results are the same for both the FORA G30 and the Clever Chek TD-4230.
## Alternate Site Testing Comparison:
This study was performed in accordance with NCCLS EP9-A and ISO 15197. 120 lay users at 3 different locations tested themselves using each alternate site with the FORA G30 blood glucose meter. Lay users were given the user manual in English, and were given no additional instructions. The lay user then obtained a fingertip blood sample, and the fingertip glucose result was compared to the AST glucose result.
{10}
The results are as follows:
Glucose Concentration $< 75\mathrm{mg / dL}$
| AST Sites | Difference within ±5mg/dL | Difference within ±10mg/dL | Difference within ±15mg/dL |
| --- | --- | --- | --- |
| Palm | 41%(11/27) | 93%(25/27) | 100%(27/27) |
| Forearm | 67%(18/37) | 96%(26/27) | 96%(26/27) |
| Upper arm | 59%(16/27) | 89%(24/27) | 100%(27/27) |
| Calf | 48%(13/27) | 85%(23/27) | 96%(26/27) |
| Thigh | 37%(10/27) | 85%(23/27) | 100%(27/27) |
Glucose Concentration $\geq 75\mathrm{mg / dL}$
| AST Sites | Difference within ±5 % | Difference within ±10 % | Difference within ±15 % | Difference within ±20 % |
| --- | --- | --- | --- | --- |
| Palm | 56%(52/93) | 84%(78/93) | 96%(89/93) | 100%(93/93) |
| Forearm | 34%(32/93) | 61%(57/93) | 86%(80/93) | 98%(91/93) |
| Upper arm | 39%(36/93) | 77%(72/93) | 90%(84/93) | 99%(92/93) |
| Calf | 24%(22/93) | 72%(67/93) | 89%(83/93) | 97%(90/93) |
| Thigh | 26%(24/93) | 57%(53/93) | 84%(78/93) | 98%(91/93) |
Linear Regression Analysis:
| Comparison | Range (mg/dL) | Slope and y-intercept | R square |
| --- | --- | --- | --- |
| Palm vs. finger | 40-425 | y = 0.979x + 4.0608 | 0.9866 |
| Forearm vs. finger | 40-425 | y = 1.002x + 2.3467 | 0.9708 |
| Upper arm vs. finger | 40-425 | y = 1.016x + 0.1852 | 0.9789 |
| Calf vs. finger | 40-425 | y = 0.952x + 6.3207 | 0.9745 |
| Thigh vs. finger | 40-425 | y = 0.953x + 4.8445 | 0.9661 |
{11}
The results of a Clarke error grid analysis are presented below; zone A – clinically accurate, zone B – deviating from the reference method by more than 20% but would lead to benign or no treatment.
| Zone | Palm vs. finger | Forearm vs. finger | Upper arm vs. finger | Calf vs. finger | Thigh vs. finger |
| --- | --- | --- | --- | --- | --- |
| A | 100% (120/120) | 98% (117/120) | 99% (119/120) | 97% (116/120) | 98% (118/120) |
| B | 0 | 2% (3/120) | 1% (1/120) | 3% (4/120) | 2% (2/120) |
| C | 0 | 0 | 0 | 0 | 0 |
| D | 0 | 0 | 0 | 0 | 0 |
| E | 0 | 0 | 0 | 0 | 0 |
b. Matrix comparison:
Not applicable. Capillary whole blood is the only indicated matrix.
3. Clinical studies:
a. Clinical Sensitivity:
Not Applicable.
b. Clinical specificity:
Not Applicable.
c. Other clinical supportive data (when a. and b. are not applicable):
Not Applicable.
4. Clinical cut-off:
Not Applicable.
5. Expected values/Reference range:
The sponsor included the following expected glucose values for people without diabetes in their user manual:
Fasting and before meals: 70 – 110 mg/dL (3.9 mmol/L – 6.1 mmol/L)¹
Two hours after meals: less than 140 mg/dL (7.8 mmol/L)²
Measurement result at any time of day without regard to time since last meal should be less than 200 mg/dL.³
¹) Sacks, DB in “Carbohydrates,” Burt, CA, Ashwood, ER (ed), Tietz Textbook of Clinical Chemistry, Philadelphia, WB Saunders Company, 1999.
²) ADA Clinical Practice Recommendations 2003.
³) Diabetes Care, volume 28, supplement 1, January 2005.
{12}
13
N. Instrument Name:
FORA G30 Blood Glucose Monitoring System
O. System Descriptions:
1. Modes of Operation:
Each test strip is single use and must be replaced with a new strip for additional readings.
Does the applicant’s device contain the ability to transmit data to a computer, webserver, or mobile device?:
Yes ☐ X (reviewed under k070941) or No ☐
Does the applicant’s device transmit data to a computer, webserver, or mobile device using wireless transmission?:
Yes ☐ X or No ☐
2. Software:
FDA has reviewed applicant’s Hazard Analysis and software development processes for this line of product types:
Yes ☐ X or No ☐
3. Specimen Identification:
There is no sample identification function with this device. Samples are applied directly to the test strip as they are collected.
4. Specimen Sampling and Handling:
This device is intended to be used with capillary whole blood, which can be applied directly to the test strip.
5. Calibration:
The device is designed to be used with Taidoc Technology Corporation’s “no coding” test strips. These strips are identified with a “38” printed on the test strip vial as the lot code. Other types of test strips should not be used with the device. No further calibrations are required of the user.
6. Quality Control:
The sponsor has three levels of controls available for this meter. A normal control is supplied with the device, but low and high levels must be purchased separately. When a test strip is inserted into the meter, a control can be run by pushing the “QC” button. An acceptable range for each control level is printed on the test strip vial label.
P. Other Supportive Instrument Performance Characteristics Data Not Covered In The “Performance Characteristics” Section above:
None.
{13}
Q. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
R. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
14
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.