The TC Matrix Clinical Chemistry Analyzer is a discrete photometric chemistry analyzer for clinical use. The device is intended to duplicate manual analytical procedures by automatically various steps such as pipetting, heating, and measuring color intensity. This device is intended for use in conjunction with certain materials to measure a variety of analytes of clinical interest in serum, plasma samples. TECO MULTI Calibrator is intended for the calibration of quantitative assays. Teco Albumin reagent is intended to measure the albumin concentration in serum and plasma. Albumin measurements are used in the diagnosis and treatment of numerous diseases involving primarily the liver or kidneys. Teco ALT reagent is intended to measure the activity of the enzyme alanine amino transferase (ALT) (also known as a serum glutamic pyruvic transaminase or SGPT) in serum and plasma. Alanine amino transferase measurements are used in the diagnosis and treatment of certain liver diseases (e.g., viral hepatitis and cirrhosis) and heart diseases. Teco Glucose reagent is intended for the quantitative determination of total glucose in human serum or plasma. 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. Teco BUN reagent is intended to measure urea nitrogen (an end-product of nitrogen metabolism) in serum or plasma. Measurements obtained by this device are used in the diagnosis and treatment of certain renal and metabolic diseases.
Device Story
TC Matrix Clinical Chemistry Analyzer is a discrete photometric system for clinical laboratory use. It automates manual analytical procedures including sample pipetting, heating, and colorimetric intensity measurement. The device processes serum and plasma samples to quantify specific analytes (Albumin, ALT, Glucose, BUN) using associated reagents and calibrators. Operated by laboratory personnel, the analyzer provides quantitative results to assist clinicians in diagnosing and managing liver, renal, and metabolic diseases. The system replaces manual benchtop methods with automated workflow to improve efficiency and consistency in clinical chemistry testing.
Clinical Evidence
No clinical data provided; device relies on bench testing and performance verification of analytical procedures.
Technological Characteristics
Discrete photometric chemistry analyzer; utilizes automated pipetting, heating, and colorimetric measurement modules. Designed for clinical laboratory environment. Connectivity and specific software architecture details not provided.
Indications for Use
Indicated for clinical use to measure analytes (Albumin, ALT, Glucose, BUN) in human serum and plasma samples for the diagnosis and treatment of liver, kidney, metabolic, and carbohydrate disorders.
Regulatory Classification
Identification
A discrete photometric chemistry analyzer for clinical use is a device intended to duplicate manual analytical procedures by performing automatically various steps such as pipetting, preparing filtrates, heating, and measuring color intensity. This device is intended for use in conjunction with certain materials to measure a variety of analytes. Different models of the device incorporate various instrumentation such as micro analysis apparatus, double beam, single, or dual channel photometers, and bichromatic 2-wavelength photometers. Some models of the device may include reagent-containing components that may also serve as reaction units.
Submission Summary (Full Text)
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1
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number:
k073370
B. Purpose for Submission:
Clearance of a new device.
C. Measurand:
Alanine amino transferase (ALT/SGPT), Albumin, Urea nitrogen (BUN), Glucose
D. Type of Test:
Photometric
E. Applicant:
TECO Diagnostics
F. Proprietary and Established Names:
TC Matrix Clinical Chemistry Analyzer
G. Regulatory Information:
1. Regulation section:
21 CFR § 862.1030, Alanine amino transferase (ALT/SGPT) test system
21 CFR § 862.1035, Albumin test system
21 CFR § 862.1770, Urea nitrogen test system
21 CFR § 862.1345, Glucose test system
21 CFR § 862.1150, Calibrator, multi-analyte mixture
21 CFR § 862.2160, Discrete photometric chemistry analyzer for clinical use
2. Classification:
Class I, subject to the limitations of exemption in 862.9(c)(4)
Class II
Class II
Class II
Class II
Class I
3. Product code:
CKA
CIX
CDQ
CGA
JIX
JJE
4. Panel:
75 (Clinical Chemistry)
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H. Intended Use:
1. Intended use(s):
See indications for use below.
2. Indication(s) for use:
The TC Matrix Clinical Chemistry Analyzer is a discrete photometric chemistry analyzer for clinical use. The device is intended to duplicate manual analytical procedures by automatically performing various steps such as pipetting, heating, and measuring color intensity. This device is intended for use in conjunction with certain materials to measure a variety of analytes of clinical interest in serum, plasma samples.
TECO MULTI Calibrator is intended for the calibration of quantitative assays.
Teco Albumin reagent is intended to measure the albumin concentration in serum and plasma. Albumin measurements are used in the diagnosis and treatment of numerous diseases involving primarily the liver or kidneys.
Teco ALT reagent is intended to measure the activity of the enzyme alanine amino transferase (ALT) (also known as a serum glutamic pyruvic transaminase or SGPT) in serum and plasma. Alanine amino transferase measurements are used in the diagnosis and treatment of certain liver diseases (e.g., viral hepatitis and cirrhosis) and heart diseases.
Teco Glucose reagent is intended for the quantitative determination of total glucose in human serum or plasma. 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.
Teco BUN reagent is intended to measure urea nitrogen (an end-product of nitrogen metabolism) in serum, and plasma. Measurements obtained by this device are used in the diagnosis and treatment of certain renal and metabolic diseases.
3. Special conditions for use statement(s):
For prescription use.
4. Special instrument requirements:
TC Matrix Clinical Chemistry Analyzer
I. Device Description:
TC Matrix Clinical Chemistry Analyzer is an automated system intended for the in vitro determination of variety of general chemistries in biological fluid such as serum or plasma. The analyzer operates in conjunction with reagents and calibrators designed for use with the system. The instrument automatically delivers samples to the reaction cuvette along with reagents and reaction constituents. The system analyzes up to 40 samples per run with up to 19 analytes (double reagents) or 38 analytes (single reagent). Major hardware components include a sample/reagent disk, dispenser, mixer, reaction Disk and photometric system.
J. Substantial Equivalence Information:
1. Predicate device name(s):
Beckman Coulter Synchron CX Delta Clinical System
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2. Predicate 510(k) number(s): k950958
3. Comparison with predicate:
| Similarities | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Intended use | The TC Matrix Clinical Chemistry Analyzer is a discrete photometric chemistry analyzer for clinical use. The device is intended to duplicate manual analytical procedures by automatically various steps such as pipetting, heating, and measuring color intensity. This device is intended for use in conjunction with certain materials to measure a variety of analytes of clinical interest in serum, plasma. | The Synchron CX Delta Clinical System is a fully automated, computer controlled, clinical chemistry analyzer intended for the in vitro quantitative measurement of a variety of analytes of clinical interest in biological fluid, such as, serum, plasma, urine, and cerebral spinal fluid. |
| User Interface | Keyboard Control | Keyboard Control, Barcode Scanner |
| Reaction Vessels | Hard plastic cuvettes and plastic reaction vessels | Hard plastic cuvettes and plastic reaction vessels |
| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Sample Type | Serum, Plasma | Serum, Plasma, Urine, Cerebrospinal Fluid |
| Detection Technologies | Photometric | Photometric, turbidimetric, multisensor electrodes, ion selective |
| Throughtput | 200 tests/Hour | 900 tests/Hour |
K. Standard/Guidance Document Referenced (if applicable):
CLSI EP5-A: Evaluation of Precision Performance of Clinical Chemistry Devices
CLSI EP6-A: Evaluation of Linearity of Quantitative Analytical Methods
CLSI EP7-A2: Method Comparison and Bias Estimation Using Patient Samples
L. Test Principle:
Albumin:
Bromcresol purple (BCP), an ionic dye, binds tightly to albumin when serum is added. The albumin- BCP complex absorbs light at 600 nm more intensively than BCP alone. The system monitors the change in absorbance at 600 nanometers. This change in absorbance is
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directly proportional to the concentration of albumin in the sample and is used by the TC Matrix System to calculate and express albumin concentration.
## ALT:
ALT converts L-Alanine and $\alpha$-ketoglutaric acid to pyruvate and glutamate. Pyruvate, NADH, and $\mathrm{H^{+}}$ are then converted by lactate dehydrogenase to lactate, $\mathrm{NAD^{+}}$, and water. The system monitors the change in $\mathrm{NAD^{+}}$ absorbance at 340 nanometers. This change in absorbance is directly proportional to the activity of alanine aminotransferase in the sample and is used by the TC Matrix System to calculate and express alanine aminotransferase activity.
## BUN:
Urea is hydrolyzed by urease to produce ammonia. The ammonia is then coupled with $\alpha$-ketoglutarate and NADH to produce glutamate and $\mathrm{NAD^{+}}$. The rate of absorbance decrease is directly proportional to the amount of urea present in the sample. The system monitors the change in absorbance at 340 nanometers. This change in absorbance is directly proportional to the concentration of urea in the sample and is used by the TC Matrix System to calculate and express the urea concentration.
## Glucose:
$\beta$-D-Glucose is oxidized by glucose oxidase to produce D-gluconic acid and hydrogen peroxide. The hydrogen peroxide is then oxidatively coupled with 4-aminoantipyrine and phenol substitute, $\mathsf{p}\neg \mathsf{HBS}$, in the presence of peroxidase to yield a red quinoneimine dye. The amount of colored complex formed is proportional to glucose concentration and can be photometrically measured.
## M. Performance Characteristics (if/when applicable):
### 1. Analytical performance:
#### a. Precision/Reproducibility:
Within and between-batch precision:
Three levels of commercial controls were used each repeatedly measured 20 times over 8 hours.
| Test Name | Control 1 | | | |
| --- | --- | --- | --- | --- |
| | Range | Mean | SD | CV% |
| Glucose | 52-72 | 62.35 | 1.14 | 1.8 |
| ALT | 20-30 | 24.9 | 0.79 | 3.2 |
| Albumin | 2.2-2.6 | 2.34 | 0.06 | 2.6 |
| BUN | 13-19 | 16.05 | 0.6 | 3.8 |
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| | Control 2 | | | |
| --- | --- | --- | --- | --- |
| | Range | Mean | SD | CV% |
| Glucose | 112- | 122.65 | 1.5 | 1.2 |
| ALT | 74-86 | 79.4 | 0.88 | 1.1 |
| Albumin | 2.9-3.5 | 3.26 | 0.06 | 1.8 |
| BUN | 35-47 | 40.25 | 0.85 | 2.1 |
| | Control 3 | | | |
| | Range | Mean | SD | CV% |
| Glucose | 336- | 364.1 | 2.47 | 0.7 |
| ALT | 155- | 166.75 | 1.52 | 0.9 |
| Albumin | 3.7-4.5 | 4.07 | 0.07 | 1.8 |
| BUN | 61-81 | 69.2 | 0.95 | 1.4 |
Run to Run Precision:
Three levels of commercial controls were used each repeatedly measured 5 times per day, continuously for 5 days, for a total of 25 repeats.
| Test Name | Control 1 | | | |
| --- | --- | --- | --- | --- |
| | Range | Mean | SD | CV% |
| Glucose | 52-72 | 61.92 | 1.38 | 2.2 |
| ALT | 20-30 | 25.24 | 0.83 | 3.3 |
| Albumin | 2.2-2.6 | 2.33 | 0.05 | 2.2 |
| BUN | 13-19 | 16.36 | 0.49 | 3 |
| | Control 2 | | | |
| | Range | Mean | SD | CV% |
| Glucose | 112- | 123.24 | 2.54 | 2.1 |
| ALT | 74-86 | 78.88 | 0.97 | 1.2 |
| Albumin | 2.9-3.5 | 3.23 | 0.07 | 2.3 |
| BUN | 35-47 | 41.44 | 1.04 | 2.5 |
| | Control 3 | | | |
| | Range | Mean | SD | CV% |
| Glucose | 336- | 361.36 | 5.3 | 1.5 |
| ALT | 155- | 167.52 | 1.83 | 1.1 |
| Albumin | 3.7-4.5 | 4.08 | 0.06 | 1.4 |
| BUN | 61-81 | 69.08 | 2.18 | 3.2 |
b. Linearity/assay reportable range:
Linearity studies were designed using CLSI EP6. Each analyte was tested with a commercial linearity kit. Each concentration was tested two times to determine the mean concentration. The results of this study demonstrate that the measuring range of Glucose is 25 to $500\mathrm{mg / dL}$ ; Albumin is 1.0 to $7.0\mathrm{mg / dL}$ ; BUN is $5.0 - 80\mathrm{mg / dl}$ ; and
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ALT is 5 to 400 IU/L. Linear regression statistics and data is summarized below:
Albumin
| Level | Concentration
g/dL | Rep(1)
g/dL | Rep.(2)
g/dL |
| --- | --- | --- | --- |
| A | 1.0 | 1.0 | 1.0 |
| B | 2.0 | 1.9 | 2.0 |
| C | 3.0 | 3.1 | 3.0 |
| D | 4.5 | 4.4 | 4.6 |
| E | 5.0 | 5.2 | 5.2 |
| F | 6.0 | 5.9 | 6.0 |
| G | 7.0 | 6.8 | 6.9 |
| Level | Mean
g/L | Difference
g/L | Difference% |
| --- | --- | --- | --- |
| A | 1.0 | 0.0 | 0.0 |
| B | 1.95 | -0.05 | -2.5 |
| C | 3.05 | 0.05 | 1.6 |
| D | 4.5 | 0.0 | 0.0 |
| E | 5.2 | 0.2 | 0.4 |
| F | 5.95 | -0.05 | -0.8 |
| G | 6.85 | -0.15 | -2.1 |
Linear Regression Analysis: $y = 1.0x + 0.027$
R Square: 1.00
BUN
| Level | Concentration
mg/dL | Rep.(1)
mg/dL | Rep.(2)
mg/dL |
| --- | --- | --- | --- |
| A | 5.0 | 5.2 | 5.1 |
| B | 12.5 | 13.1 | 12.9 |
| C | 25.0 | 23.8 | 23.1 |
| D | 50.0 | 48.5 | 48.1 |
| E | 80.0 | 78.5 | 78.1 |
| Level | Mean
mg/dL | Difference
mg/dL | Difference% |
| --- | --- | --- | --- |
| A | 5.15 | 0.15 | 3.0 |
| B | 13.0 | 0.5 | 4.0 |
| C | 23.45 | -1.55 | -6.2 |
| D | 48.3 | -1.7 | -3.4 |
| E | 78.3 | -1.7 | -2.1 |
Linear Regression Analysis: $y = 0.95x + 0.42$
R Square: 0.99
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Glucose
| Level | Concentration mg/dL | Rep.(1) mg/dL | Rep.(2) mg/dL |
| --- | --- | --- | --- |
| A | 25 | 26 | 26 |
| B | 50 | 51 | 52 |
| C | 100 | 98 | 98 |
| D | 200 | 201 | 204 |
| E | 300 | 294 | 295 |
| F | 400 | 391 | 389 |
| G | 500 | 495 | 497 |
| Level | Mean mg/dL | Difference mg/dL | Difference % |
| --- | --- | --- | --- |
| A | 26.0 | 1.0 | 4.0 |
| B | 51.5 | 1.5 | 3.0 |
| C | 98.0 | -2.0 | -2.0 |
| D | 202.5 | 2.5 | 1.25 |
| E | 294.5 | -5.5 | -1.8 |
| F | 390.0 | -10 | -2.5 |
| G | 496.0 | -4.0 | -0.8 |
Linear Regression Analysis: $y = 0.98x + 2.15$
R Square: 1.00
ALT
| Level | Concentration IU/L | Rep(1) IU/L | Rep(2) IU/L |
| --- | --- | --- | --- |
| A | 5 | 5 | 6 |
| B | 25 | 24 | 25 |
| C | 75 | 74 | 76 |
| D | 200 | 198 | 195 |
| E | 300 | 295 | 291 |
| F | 400 | 391 | 394 |
| Level | Mean IU/L | Difference IU/L | Difference % |
| --- | --- | --- | --- |
| A | 5.5 | 0.5 | 10.0 |
| B | 24.5 | -0.5 | -2.0 |
| C | 75.0 | 0.0 | 0.0 |
| D | 196.5 | -3.5 | -1.75 |
| E | 293.0 | -7.0 | -2.3 |
| F | 392.5 | -7.5 | -1.9 |
Linear Regression Analysis: $y = 0.98x + 0.66$
R Square: 1.00
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c. Traceability, Stability, Expected values (controls, calibrators, or methods): The calibrators for the assays are traceable to an in house solution using commercial components. The calibrator target values are glucose: $200\mathrm{mg/dL}$ , urea: $45\mathrm{mg/dL}$ , and albumin: $3.0\mathrm{g/dL}$ . The glucose, BUN, and albumin solutions are run 20 times to get the mean as TC Multi-Cal target value. Stability studies showed the shelf-life of TC Multi-Calibrator is 24 months. For ALT, there is no calibration required as the analyzer calculates the activity by using a constant factor times the change in absorbance per minute after adding sample.
# d. Detection limit:
Analytical minimal detectable concentration is defined by the sponsor as replicates of a concentration that falls within a calculated range (the mean of the samples run plus and minus two standard deviations). The minimal detectable limit of Teco BUN, Albumin, ALT and Glucose reagents were investigated by reading the change for Distilled Water as the zero sample and a known concentration (diluted the lowest level of a commercial linearity set) on TC Matrix Chemistry Analyzer. Teco BUN, Albumin, ALT and Glucose Reagents on TC Matrix showed little or no reagent drift on the zero samples. Teco BUN, Albumin, ALT and Glucose Reagents showed known concentration of BUN $5.0\mathrm{mg / dL}$ ; Albumin $1.0\mathrm{g / dL}$ ; ALT $5.0\mathrm{U / L}$ and Glucose $25\mathrm{mg / dL}$ as the minimal detectable limit.
# e. Analytical specificity:
Interference Studies were designed using CLSI EP7-A. Studies were performed to assess common or known substances that could interfere with Teco BUN, Albumin, ALT and Glucose Reagent Sets on TC Matrix. The following substances were tested for interference and Limitations. Interference study was demonstrated in a study using serum samples spiked with interferants.
| BUN | Sample 1 | Sample 2 | Sample 3 |
| --- | --- | --- | --- |
| Without interferants | | | |
| Replicate 1 | 10 | 37 | 68 |
| Replicate 2 | 9 | 36 | 67 |
| Replicate 3 | 10 | 37 | 68 |
| Mean | 9.7 | 36.7 | 67.7 |
| Hemoglobin 150mg/dl | | | |
| Replicate 1 | 10 | 36 | 65 |
| Replicate 2 | 11 | 36 | 66 |
| Replicate 3 | 10 | 35 | 67 |
| Mean | 10.3 | 35.7 | 66 |
| Conclusion | NSI | NSI | NSI |
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| Bilirubin 30mg/dl | | | |
| --- | --- | --- | --- |
| Replicate 1 | 10 | 37 | 66 |
| Replicate 2 | 9 | 36 | 67 |
| Replicate 3 | 10 | 36 | 65 |
| Mean | 9.7 | 36.3 | 66 |
| Conclusion | NSI | NSI | NSI |
| Triglyceride 1800mg/dl | | | |
| Replicate 1 | 10 | 37 | 68 |
| Replicate 2 | 10 | 36 | 66 |
| Replicate 3 | 9 | 36 | 67 |
| Mean | 9.67 | 36.33 | 67 |
| Conclusion | NSI | NSI | NSI |
NSI= No Significant Interference (within ±10%)
| Albumin | Sample 1 | Sample 2 | Sample 3 |
| --- | --- | --- | --- |
| Without interferants | | | |
| Replicate 1 | 1.7 | 3.4 | 6.4 |
| Replicate 2 | 1.6 | 3.3 | 6.6 |
| Replicate 3 | 1.7 | 3.4 | 6.5 |
| Mean | 1.7 | 3.37 | 6.5 |
| Hemoglobin 100mg/dl | | | |
| Replicate 1 | 1.5 | 3.3 | 6.5 |
| Replicate 2 | 1.6 | 3.4 | 6.6 |
| Replicate 3 | 1.6 | 3.3 | 6.5 |
| Mean | 1.6 | 3.3 | 6.5 |
| Conclusion | NSI | NSI | NSI |
| Bilirubin 30mg/dl | | | |
| Replicate 1 | 1.6 | 3.4 | 6.4 |
| Replicate 2 | 1.7 | 3.5 | 6.6 |
| Replicate 3 | 1.6 | 3.4 | 6.7 |
| Mean | 1.6 | 3.4 | 6.6 |
| Conclusion | NSI | NSI | NSI |
| Triglyceride 1800mg/dl | | | |
| Replicate 1 | 1.6 | 3.4 | 6.5 |
| Replicate 2 | 1.6 | 3.5 | 6.5 |
| Replicate 3 | 1.5 | 3.3 | 6.6 |
| Mean | 1.6 | 3.4 | 6.5 |
| Conclusion | NSI | NSI | NSI |
NSI= No Significant Interference (within ±10%)
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| ALT | Sample 1 | Sample 2 | Sample 3 |
| --- | --- | --- | --- |
| Without interferants | | | |
| Replicate 1 | 15 | 39 | 367 |
| Replicate 2 | 14 | 36 | 345 |
| Replicate 3 | 14 | 37 | 356 |
| Mean | 14.3 | 37.3 | 356 |
| Hemoglobin 150mg/dl | | | |
| Replicate 1 | 15 | 38 | 347 |
| Replicate 2 | 14 | 39 | 338 |
| Replicate 3 | 15 | 37 | 345 |
| Mean | 14.7 | 38 | 343.3 |
| Conclusion | NSI | NSI | NSI |
| Bilirubin 30mg/dl | | | |
| Replicate 1 | 16 | 39 | 365 |
| Replicate 2 | 15 | 35 | 367 |
| Replicate 3 | 15 | 36 | 378 |
| Mean | 15.3 | 36.7 | 370 |
| Conclusion | NSI | NSI | NSI |
| Triglyceride 1800mg/dl | | | |
| Replicate 1 | 16 | 38 | 375 |
| Replicate 2 | 15 | 36 | 371 |
| Replicate 3 | 15 | 38 | 369 |
| Mean | 15.3 | 37.3 | 371.7 |
| Conclusion | NSI | NSI | NSI |
NSI= No Significant Interference (within ± 20%)
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| Glucose | Sample 1 | Sample 2 | Sample 3 |
| --- | --- | --- | --- |
| Without interferants | | | |
| Replicate 1 | 34 | 98 | 425 |
| Replicate 2 | 33 | 95 | 416 |
| Replicate 3 | 35 | 94 | 421 |
| Mean | 34 | 95.7 | 420.7 |
| Hemoglobin 150mg/dl | | | |
| Replicate 1 | 36 | 96 | 420 |
| Replicate 2 | 35 | 94 | 429 |
| Replicate 3 | 34 | 95 | 418 |
| Mean | 35 | 95 | 422.3 |
| Conclusion | NSI | NSI | NSI |
| Bilirubin 30mg/dl | | | |
| Replicate 1 | 33 | 97 | 424 |
| Replicate 2 | 35 | 96 | 421 |
| Replicate 3 | 34 | 95 | 422 |
| Mean | 34 | 96 | 422.3 |
| Conclusion | NSI | NSI | NSI |
| Triglyceride 1800mg/dl | | | |
| Replicate 1 | 35 | 94 | 432 |
| Replicate 2 | 34 | 96 | 435 |
| Replicate 3 | 36 | 95 | 419 |
| Mean | 35 | 95 | 428.7 |
| Conclusion | NSI | NSI | NSI |
NSI= No Significant Interference (within ± 10%)
f. Assay cut-off: Not Applicable
2. Comparison studies:
a. Method comparison with predicate device:
Seventy serum samples covering the assay ranges were used in a method comparison study using CLSI EP9-A2 with the TC Matrix Clinical Chemistry Analyzer compared to a reference method. In order to ensure the claimed ranges were covered for ALT, albumin, glucose and BUN, 4 samples were spike and 2 were diluted. The linear regression information is summarized in the table below.
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| Test Name | Correlation Coefficient (R2) | Regression |
| --- | --- | --- |
| ALT | 0.99 | y = 1.01x - 0.19 |
| Albumin | 0.95 | y = 1.05x - 0.17 |
| Glucose | 0.99 | y = 0.99x + 2.6 |
| BUN | 0.98 | y = 1.02x - 0.06 |
# b. Matrix comparison:
Twenty matched serum samples covering the assay ranges were used in a matrix comparison study with the serum samples compared to EDTA plasma samples. In order to ensure the claimed ranges were covered for ALT, albumin, glucose and BUN, 2 samples were spike and 1 was diluted. The linear regression is summarized in the table below.
| Test Name | Correlation Coefficient (R2) | Regression |
| --- | --- | --- |
| ALT | 0.99 | y = 1.0x - 0.69 |
| Albumin | 0.96 | y = 1.01x - 0.06 |
| Glucose | 0.99 | y = 1.02x - 2.6 |
| BUN | 0.98 | y = 0.98x + 1.01 |
# 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:
ALT:
10 - 40 IU/L
Tietz, N.W., Fundamentals of Clin. Chem., Philadelphia, W.B. Saunders (1970).
Glucose:
70 - 105 mg/dl
The sponsor strongly recommends each laboratory establish its own normal range.
Tietz, N.W., Fundamentals of Clin. Chem., Philadelphia, W.B. Saunders (1970).
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ALB:
3.5-5.0g/dL or 35~50 g/L
Tietz, N.W., Fundamentals of Clin. Chem., Philadelphia, W.B. Saunders (1970).
BUN:
15 - 38 mg/dL or 2.5 to 6.4 mmol/L
Wildmann, F.K.: Coodales Clinical Interpretation Laboratory Tests. F.A. Davis Co., Philadelphia (1969).
N. Instrument Name:
TC Matrix Clinical Chemistry Analyzer
O. System Descriptions:
1. Modes of Operation:
The instrument has a single mode of operation.
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:
Sample identification is performed through an interface which instructs the device which sample types are present and where on the carousel they are placed.
4. Specimen Sampling and Handling:
This device is intended to be used with serum or plasma. The sponsor recommends sample handling procedures in the package inserts of the assays.
5. Calibration:
Calibration on the analyzer used the TECO MULTI Calibrator. The system must have a valid calibration in memory before controls or patient samples can be run, and the system will automatically perform checks on the calibration and produce data at the end of calibration.
6. Quality Control:
The sponsor recommends that each laboratory establish their frequency of control determination and that quality control requirements should be performed in conformance with local, state, and/or Federal regulations or accreditation requirements.
P. Other Supportive Instrument Performance Characteristics Data Not Covered In The "Performance Characteristics" Section above:
None
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
13
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substantial equivalence decision.
14
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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.