The Sirrus® Clinical Chemistry Analyzer is a discrete photometric chemistry analyzer for clinical use. The device is intended to duplicate manual analytical procedures by performing 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.
Device Story
Sirrus Clinical Chemistry Analyzer; automated system for quantitative clinical chemistry analysis. Device performs automated pipetting, heating, and photometric color intensity measurement to quantify analytes. Used in clinical settings by laboratory personnel. Input: clinical samples and reagents; Output: quantitative analyte concentrations (e.g., Glucose, Cholesterol, Triglycerides). System automates manual laboratory workflows; results used by clinicians for diagnostic decision-making. Benefits include increased efficiency and consistency in clinical chemistry testing compared to manual methods.
Discrete photometric chemistry analyzer. Light source: tungsten halogen lamp. Detector: photo-diode. Wavelength range: 340-800 nm. Cuvettes: semi-disposable plastic (8 mm path length), automatic washing system. Pipetting: plunger driven by stepping motor with level sensing. Connectivity: Bar Code ID (39/128). Calibration: Factor, Linear, Logit-log, Spline, Exponential, Polynomial. Quality Control: Levy-Jennings, Westgard Multi-Rule.
Indications for Use
Indicated for clinical use in measuring analytes including glucose, cholesterol, and triglycerides in patient samples.
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.
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# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number:
k042169
B. Purpose for Submission:
New 510(k) for instrument – instrument performance was established with previously 510(k) cleared assays (see k011900, k831863 and k831858).
C. Measurand:
Glucose
Cholesterol
Triglycerides
D. Type of Test:
Quantitative Photometric
E. Applicant:
Stanbio Laboratory
F. Proprietary and Established Names:
Stanbio Laboratory Sirrus® Clinical Chemistry Analyzer
G. Regulatory Information:
1. Regulation section:
21CFR Sec - 862.1345 - Glucose test system
21CFR Sec - 862.1175 - Cholesterol (total) test system
21CFR Sec - 862.1705 - Triglyceride test system
21CFR Sec.-862.2160 - Discrete photometric chemistry analyzer for clinical use
2. Classification:
Class 2
3. Product code:
CGA - Glucose oxidase, glucose
CHH - Enzymatic esterase--oxidase, cholesterol
CDT - Lipase hydrolysis/glycerol kinase enzyme, triglycerides
JJE - Analyzer, chemistry (photometric, discrete), for clinical use
4. Panel:
Chemistry (75)
H. Intended Use:
1. Intended use(s):
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See Indication(s) for use below
2. **Indication(s) for use:**
The Sirrus® 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 to include Glucose, Cholesterol, and Triglycerides.
3. **Special conditions for use statement(s):**
For prescription use
4. **Special instrument requirements:**
Stanbio Laboratory Sirrus® Clinical Chemistry Analyzer
I. **Device Description:**
The system is composed of the following units. They are sampler, sample delivery, reagent tray, reagent delivery, reaction tray, mixing units, cuvette washing unit, spectrophotometer, etc. A complete list is present in the operator’s manual.
The sample cups/tubes with the sample in it are set in the sample tray, and the reagent bottles are set in the reagent tray. Test orders for these samples are entered in the Order Entry screen. When the start button is clicked the cuvette washing unit starts cleaning from the No.1 cuvette. Before the last step of cuvette cleaning, water blank is measured. When the reaction tray rotates and the cuvette passes the optical measurement position, light absorption data of 1 or 2 wavelengths are measured. These data are the basis of optical absorption (Absorption = 0) to the following optical absorption measurement. After the water blank measurement, de-ionized water is aspirated out and the inside of cuvette is wiped out. When No.1 cuvette advances to one step before the R1 dispensation position, the reagent tray rotates and transports the reagent bottle to the reagent aspiration position.
Next, R1 probe moves to the aspiration position, above the reagent bottle, then moves down to the reagent level. This probe has a level sensing function and it stops when the probe tip touches the reagent. The designated amount of reagent is aspirated by the reagent pump. Next, R1 probe goes up and moves to the R1 dispensation position and waits for the cuvette coming to the dispensation position. When the cuvette comes to the position, R1 probe goes down to the designated level and dispenses the reagent. Then, R1 probe moves to the probe washing pot and both inside and outside are washed by de-ionized water there. After that, the residual water droplets are wiped out. At the 5th cycle after the R1 dispensation, the sample tray rotates to transfer No.1 sample cup/tube to the sampling position. The sample probe moves above the sample cup then goes down. The sample probe also has a level sensing function, and stops at the sample level. The designated amount of sample is aspirated
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by the sample pump. Then the sample probe moves above No.1 cuvettes and goes down to the R1 reagent level in the cuvette, and dispenses the sample. After dispensation, the probe goes up. At the next cycle, the cuvette is moved to the mixing station-1, where R1 and the sample are mixed by MU-1, the mixing unit. This mixing is repeated in the next cycle, two times in total. The sample probe moves to the probe washing pot and both inside and outside are washed with de-ionized water, there. After that, the residual water droplets are wiped out. After R1 and the sample are mixed, optical measurement starts. When the reaction tray rotates and the cuvette passes the optical measurement position, light absorption data of 12 wavelengths are measured. After 5 minutes of R1 dispensation, the cuvette moves to R2 dispensation position, the same position as R1 dispensation, and then R2 is dispensed by R2 probe, which has the same function as R1 probe. After dispensation, R2 probe goes up. At the next cycle, the cuvette is moved to the mixing station-1, where R2 and the reaction liquid are mixed by MU-1. This mixing is repeated in the next cycle, two times in total. R2 probe moves to the probe washing pot and both inside and outside are washed with de-ionized water. After that, the residual water droplets are removed. After 4 minutes of R2 dispensation, the cuvette comes to the mixing station-2, where the particles in the reaction liquid are dispersed again by MU-2. (Mixing before the measurement is done by request.) After 10.7 minutes of sample dispensation, the reaction liquid in the cuvette is aspirated out by the No.1 nozzle of the cuvette washing unit and transferred to the drainage reservoir, outside of the system.
As the last step of the measurement for the 1st test of No. 1 sample, optical absorption data are converted into concentration or activity data using calibration curve. But the test results will not be printed out till the whole test results of No.1 sample are obtained. The same process is repeated for the 2nd, 3rd... test items, and the 2nd, 3rd... sample.
An optional ISE component is available and was cleared under 510(k), k040958.
See k011900, k831863 and k831858 for a description of the assays.
J. Substantial Equivalence Information:
1. Predicate device name(s): Roche Cobas Mira Plus®
2. Predicate 510(k) number(s): k920402
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3. Comparison with predicate:
| | Sirrus® | Cobas Mira Plus® |
| --- | --- | --- |
| General | | |
| System Principle | Discrete, single line random access, multi-test analysis | Random access, sample selective analysis |
| Throughput | 240 tests per hour | 132 tests per hour |
| Configuration | Analytical unit, Control Unit | Self contained analytical unit and control unit |
| | | |
| Optical Measurement Unit | | |
| Measurement Modes | Absorbance | Absorbance |
| Detector | Photo-diode | Filter photometer |
| Optical System | Wavelength range of 340 to 800 nm | Wavelength range of 340 to 600 nm |
| Filters | 340,380,405,450,505,546,570,600,660,700,750, and 800 nm | 340, 405, 500, 550, and 600 nm |
| Linear absorbance range | 0 – 2.5 A at 340 nm | 0 – 2.4 A at 340 nm |
| Light Source | Tungsten halogen lamp | Xenon flash tube |
| | | |
| Data Processing | | |
| Calibration curve | Factor, Linear, Logit-log 1, Logit-log 2, Spline, Exponential, Polynomial | Factor, Linear, Polynomial |
| Reaction Unit | | |
| Cuvettes | Plastics, semi disposable (Replace at 6 months, machine notification) | Plastics, disposable |
| Number of cuvettes | 60 (Washed between tests) | 72 (Disposable) |
| Cuvette washing | Automatic washing system in 10 operating steps. Reaction waste is aspirated out (1 step), cuvette is washed repeatedly (7 steps, (1 alkaline wash, 1 acidic wash, 5 deionized water washes)), and then residual liquid is removed (2 steps). | N/A |
| Path length | 8 mm | 6 mm |
| Volume | 840 μL | 600 μL |
| Reagent Volume | 400 μL max | 600 μL max |
| | | |
| Sample/Reagent Delivery | | |
| Pipetting System | Plunger driven by stepping motor | XYZ pipetting system |
| Sample Dispense | Sample volume: 3 – 30 μL; 0.5 μL step | Sample volume: 2 – 95 μL; 0.1 μL step |
| Reagent Dispense | Reagent volume: 20 – 350 μL, 5 μL step | Reagent volume: 100 – 600 μL; 1 μL step |
| | | |
K. Standard/Guidance Document Referenced (if applicable):
NCCLS EP5-A: Evaluation of Precision Performance of Clinical Chemistry Devices; Approved Guideline
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FDA guidance document "Guide for the Content of Premarket Submission for Software Contained in Medical Devices."
## L. Test Principle:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
## M. Performance Characteristics (if/when applicable):
### 1. Analytical performance:
#### a. Precision/Reproducibility:
Precision testing was performed according to NCCLS EP-5A. Two levels of control were tested.
Within Run:
| Assay (Sample #) | Mean | Standard Deviation | % CV |
| --- | --- | --- | --- |
| | | | |
| Glucose (#1) | 94 mg/dL | 1.57 | 1.67 % |
| Glucose (#2) | 270 mg/dL | 2.61 | 0.97 % |
| | | | |
| Cholesterol (#1) | 143 mg/dL | 1.50 | 1.05 % |
| Cholesterol (#2) | 242 mg/dL | 2.68 | 1.11 % |
| | | | |
| Triglycerides (#1) | 78 mg/dL | 1.35 | 1.73 % |
| Triglycerides (#2) | 183 mg/dL | 1.79 | 0.98 % |
Between Run:
| Assay (Sample #) | Mean | Standard Deviation | % CV |
| --- | --- | --- | --- |
| | | | |
| Glucose (#1) | 100 mg/dL | 2.23 | 2.22 % |
| Glucose (#2) | 302 mg/dL | 4.86 | 1.61 |
| | | | |
| Cholesterol (#1) | 154 mg/dL | 6.15 | 3.99 % |
| Cholesterol (#2) | 263 mg/dL | 4.17 | 1.58 % |
| | | | |
| Triglycerides (#1) | 86 mg/dL | 2.86 | 3.30 % |
| Triglycerides (#2) | 208 mg/dL | 5.56 | 2.67 % |
#### b. Linearity/assay reportable range:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
#### c. Traceability, Stability, Expected values (controls, calibrators, or methods):
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
#### d. Detection limit:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
#### e. Analytical specificity:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
#### f. Assay cut-off:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
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2. Comparison studies:
a. Method comparison with predicate device:
To demonstrate substantial equivalence between the Sirrus and the predicate device, Cobas Mira Plus®, three reagents (glucose, cholesterol, and triglyceride) with a finding of substantial equivalence (previous submissions) were tested on both instruments. A comparison was performed between the Stanbio Laboratory Sirrus® Chemistry Analyzer and the Roche Cobas Mira Plus®. A total of 53 patient samples were assayed on both instruments. The results are reported in the following table.
| Assay | Correlation Coefficient | Slope | Y-axis intercept | R Squared | Correlation Equation |
| --- | --- | --- | --- | --- | --- |
| Glucose | 0.9971 | 0.887 | 16.17 mg/dL | 0.9942 | y = 0.887x + 16.17 |
| Cholesterol | 0.9894 | 1.126 | -24.90 mg/dL | 0.9789 | y = 1.126x - 24.90 |
| Triglycerides | 0.9978 | 0.972 | -5.03 mg/dL | 0.9955 | y = 0.972x - 5.03 |
b. Matrix comparison:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
3. Clinical studies:
a. Clinical Sensitivity:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
b. Clinical specificity:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
c. Other clinical supportive data (when a. and b. are not applicable):
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
4. Clinical cut-off:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
5. Expected values/Reference range:
See k011900 (Glucose), k831863 (Cholesterol), and k831858 (Triglycerides)
N. Instrument Name:
Sirrus® Clinical Chemistry Analyzer
O. System Descriptions:
1. Modes of Operation:
Discrete, single line random access, multi-test analysis
2. Software:
FDA has reviewed applicant’s Hazard Analysis and software development processes for this line of product types:
Yes ☐ X or No ☐
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3. Specimen Identification:
Bar Code ID codes 39 and 128 format
4. Specimen Sampling and Handling:
Direct sample collection tube or sample aliquot tub
5. Calibration:
Factor, Linear, Logit-log 1, Logit-log 2, Spline, Exponential, Polynomial
6. Quality Control:
Levy-Jennings Plot, Bar Charts, Westgard Multi-Rule Chart XB-R
P. Other Supportive Instrument Performance Characteristics Data Not Covered In The "Performance Characteristics" Section above:
The software documentation was prepared in accordance with the FDA guidance document "Guide for the Content of Premarket Submission for Software Contained in Medical Devices."
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.
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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.
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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.
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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.
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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.