K103531 · Tokyo Boeki Medisys, Inc. · CFR · Dec 1, 2011 · Clinical Chemistry
Device Facts
Record ID
K103531
Device Name
PRESTIGE 24I; BIOLIS 24I; MGC 240
Applicant
Tokyo Boeki Medisys, Inc.
Product Code
CFR · Clinical Chemistry
Decision Date
Dec 1, 2011
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1345
Device Class
Class 2
Attributes
Pediatric
Indications for Use
The Biolis 24i Clinical Chemistry Analyzer is a discrete photometric clinical chemistry analyzer. The device is intended to duplicate manual analytical procedures by automating various steps such as pipetting, heating, measuring color intensity, and reporting results. The device is intended to be used with certain materials to measure various analytes of diagnostic interest including glucose. The Biolis 24i analyzer with glucose hexokinase assay is intended to measure glucose quantitatively in human serum. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic glycemia, and of the pancreatic isle cell carcinoma.
Device Story
Discrete, random-access clinical chemistry analyzer; automates pipetting, heating, and photometric measurement. Inputs: human serum samples; reagents. Principle: photometry (glucose hexokinase assay) at 340 nm; optional indirect potentiometry (ISE module) for electrolytes. Output: quantitative analyte concentrations. Used in clinical laboratory settings by trained personnel. Automates manual analytical procedures; provides rapid, standardized results for diagnostic decision-making regarding metabolic disorders. Benefits: increased throughput (240 tests/hr), reduced manual error, and consistent diagnostic data.
Clinical Evidence
Bench testing only. Precision evaluated per CLSI EP05-A2 (n=80 per sample, total imprecision 1.9-2.5% CV). Linearity (25-500 mg/dL) per EP06-A. LoD (5.64 mg/dL) and LoQ (10 mg/dL) per EP17-A. Interference testing per EP07-A2. Method comparison (n=173 serum specimens) against predicate yielded y = 0.974x + 2.22, r = 0.999.
Indicated for quantitative measurement of glucose in human serum for diagnosis and treatment of carbohydrate metabolism disorders (diabetes mellitus, neonatal hypoglycemia, idiopathic glycemia) and pancreatic islet cell carcinoma. Optional module measures sodium, potassium, and chloride in serum.
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.
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510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number:
k103531
B. Purpose for Submission:
The additional clearance of photometric capabilities to an already cleared clinical laboratory analyzer cleared for ISE methods under k040958. A previously cleared glucose reagent (k971467) was used to demonstrate performance for photometry on the instrument.
C. Measurand:
Serum glucose
D. Type of Test:
Quantitative photometric
E. Applicant:
Tokyo Boeki Medisys Inc.
F. Proprietary and Established Names:
Biolis 24i Clinical Chemistry Analyzer
G. Regulatory Information:
1. Regulation section:
21CFR Sec.-862.1345-Glucose test system.
21CFR Sec.-862.2160 Discrete photometric chemistry analyzer for clinical use.
2. Classification:
II, I respectively
3. Product code:
CFR - Hexokinase, Glucose
JJE - Analyzer, Chemistry (Photometric, Discrete), For Clinical Use
4. Panel:
Chemistry (75)
H. Intended Use:
1. Intended use(s):
See indication(s) for use below
2. Indication(s) for use:
The Biolis 24i Clinical Chemistry Analyzer is a discrete photometric clinical chemistry analyzer. The device is intended to duplicate manual analytical procedures by automating various steps such as pipetting, heating, measuring color intensity, and reporting results. The device is intended to be used with certain materials to measure various analytes of diagnostic interest including
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glucose.
The Biolis 24i analyzer with glucose hexokinase assay is intended to measure glucose quantitatively in human serum. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic glycemia, and of the pancreatic isle cell carcinoma.
3. Special conditions for use statement(s):
Prescription use
4. Special instrument requirements:
Biolis 24i Clinical Chemistry Analyzer
I. Device Description:
Using photometry, the Biolis 24i instrument measures the glucose concentration in serum by monitoring the change in absorbance at 340 nm. Additionally, the Biolis 24i with optional Ion-Selective Elective module cleared under (k040958) measures the concentration of the electrolytes, sodium, potassium and chloride in serum, using indirect potentiometry. The Biolis 24i Clinical Chemistry Analyzer will also be marketed under the trade names MGC 240 and Prestige 24i.
Reagent: Carolina Liquid Chemistries Glucose Reagent (k971467) packaged for use on the BioLis 24i analyzer contains three 40 mL bottles of GLUC R1 Reagent. GLUC R1 Reagent contains 1.1 mmol/L ATP, 2.7 mmol/L NAD, 2 mmol/L magnesium, >2000 IU/L hexokinase (yeast), >4000 IU/L, G-6-PD (leuconostoc mesenteroides), preservatives and stabilizers.
Calibration is performed using Pointe Chemistry Calibrator (k070207)
J. Substantial Equivalence Information:
1. Predicate device name(s):
Beckman's CX-7 and Glucose Hexokinase Reagent
2. Predicate 510(k) number(s):
k904219, k802810 respectively
3. Comparison with predicate:
| Item | New Device Biolis 24i | Predicate SYNCHRON CX-7 (k904219) |
| --- | --- | --- |
| Intended use | Discrete photometric clinical chemistry analyzer. The device is intended to duplicate manual analytical procedures by automating various steps such as pipetting, heating, | Same |
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| | measuring color intensity, and reporting results. | |
| --- | --- | --- |
| System Principle | Discrete, single line random access, multi-test analysis | Same |
| Throughput | 240 tests | 225 tests/hr (photometric only) |
| Configuration | Analytical unit, Control unit | Same |
| Measurement modes | Absorbance | Same |
| Detector | Photo-diode | Diffraction grating, photodiode array |
| Optical system | Wavelength range of 340 to 800nm | 340, 380, 410, 470, 520, 560, 600, 650, 670, 700 nm |
| Light source | Tungsten halogen lamp | xenon |
| Reaction cuvettes | Plastics, semi disposal | quartz |
| Path length | 8 mm | 5 mm |
| Reaction time | Maximum 10 min. | Maximum 12 min. |
| Incubation temperature | 37°C +/- 0.1°C | same |
| | | |
| Glucose | New Device
Biolis 24i | Predicate device k802810 |
| Intended use | Quantitative determination of glucose in serum | Same |
| Specimen types | serum | Serum, plasma, urine, CSF |
| Method | Photometric endpoint using glucose hexokinase. | Same |
| Sample Volume | 3 uL | same |
| Reaction Time | 5 min
Analysis time
Read period: 52 - 54 points
(15 seconds per point) | 5 min |
K. Standard/Guidance Document Referenced (if applicable):
- CLSI - Evaluation of Precision Performance of Clinical Chemistry Devices - EP05-A2
- CLSI - Evaluation of the Linearity of Quantitative Analytical Methods - EP06-A
- CLSI - Interference Testing in Clinical Chemistry - EP07-A2
- CLSI - Method Comparison and Bias Estimation Using Patient Samples - EP09-A2
- CLSI - Protocols for Determination of Limits of Detection and Limits of Quantitation - EP17-A
L. Test Principle:
The assay utilizes the enzymatic procedure using the hexokinase and glucose-6-phosphate dehydrogenase for the determination of glucose. The BioLis 24i Clinical System monitors this reaction bichromatically at 340 nm/405 nm. The increase in absorbance is directly proportional to the concentration of glucose in the specimen.
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M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Five individual serum specimens, two spiked with glucose, were assayed 15 times each on two BioLis 24i Clinical Systems with two different lots of Carolina Liquid Chemistries Glucose Reagent. Estimates of repeatability are calculated for each sample as the pooled standard deviation.
Repeatability of Glucose Measurements in mg/dL
| Sample | n | mean | SD | %CV |
| --- | --- | --- | --- | --- |
| Serum 1 | 59 | 60.3 | 0.8 | 1.3% |
| Serum 2 | 60 | 106.4 | 1.4 | 1.3% |
| Serum 3 | 60 | 116.8 | 1.4 | 1.2% |
| Serum 4 | 60 | 192.1 | 2.2 | 1.1% |
| Serum 5 | 60 | 446.2 | 6.8 | 1.5% |
Two serum pools and two control sera were assayed in duplicate over twenty days in two analytical runs per day. Assays were performed on two separate analyzers using two lots of Carolina Liquid Chemistries Glucose Reagent. Estimates of within run and total imprecision are calculated for each analyzer as described in CLSI protocol EP5.
Precision of Glucose Measurement in mg/dL
| Analyzer
Sample | n | mean | Within Run Imprecision | | Total Imprecision | |
| --- | --- | --- | --- | --- | --- | --- |
| | | | SD | %CV | SD | %CV |
| Analyzer 1 | | | | | | |
| Control 1 | 80 | 63.2 | 1.0 | 1.6% | 1.5 | 2.4% |
| Serum Pool 1 | 80 | 118.1 | 2.2 | 1.9% | 2.9 | 2.5% |
| Serum Pool 2 | 80 | 188.8 | 2.0 | 1.0% | 4.1 | 2.1% |
| Control 2 | 80 | 447.0 | 6.2 | 1.4% | 10.5 | 2.3% |
| Analyzer 2 | | | | | | |
| Control 1 | 80 | 63.2 | 1.0 | 1.6% | 1.2 | 1.9% |
| Serum Pool 1 | 80 | 117.6 | 1.7 | 1.5% | 2.7 | 2.3% |
| Serum Pool 2 | 80 | 186.9 | 2.3 | 1.2% | 3.6 | 1.9% |
| Control 2 | 80 | 445.9 | 4.8 | 1.1% | 9.8 | 2.2% |
b. Linearity/assay reportable range:
The claimed reportable range is 25 to 500 mg/dL supported by linearity, limit of quantitation and method comparison below.
Linearity
Standards ranging from 0 to 500 mg/dL were assayed in duplicate in
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ascending order over 6 individually calibrated runs. The below % difference from the expected values show acceptable linearity with no greater than 5.80 % difference in the claimed measuring range of 25 to 500 mg/dL
| Std mg/dL | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Run 6 | Mean | Diff | % Diff |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.5 | 0.0 | 0.6 | 0.6 | |
| 5 | 4.0 | 1.0 | 2.4 | 5.0 | 6.0 | 7.0 | 4.2 | -0.8 | -15.33 |
| 25 | 26.0 | 25.5 | 25.0 | 21.5 | 25.0 | 26.0 | 24.8 | -0.2 | -0.67 |
| 50 | 52.0 | 49.5 | 50.0 | 46.5 | 49.5 | 48.0 | 49.3 | -0.8 | -1.50 |
| 100 | 99.5 | 98.0 | 100.0 | 97.0 | 97.0 | 96.5 | 98.0 | -2.0 | -2.00 |
| 150 | 147.0 | 148.5 | 148.0 | 146.5 | 144.0 | 145.0 | 146.5 | -3.5 | -2.33 |
| 200 | 196.0 | 196.5 | 200.0 | 197.0 | 193.5 | 196.0 | 196.5 | -3.5 | -1.75 |
| 300 | 286.0 | 292.5 | 297.5 | 294.0 | 277.5 | 284.0 | 288.6 | -11.4 | -3.81 |
| 400 | 385.5 | 387.0 | 394.5 | 388.0 | 365.5 | 386.0 | 384.4 | -15.6 | -3.90 |
| 500 | 464.5 | 440.5 | 478.0 | 485.5 | 477.0 | 480.5 | 471.0 | -29.0 | -5.80 |
c. Traceability, Stability, Expected values (controls, calibrators, or methods): Established in k070207 for the Calibrators
d. Detection limit:
The limit of detection (LoD) for glucose is $5.64\mathrm{mg / dL}$ , determined consistent with the guidelines in CLSI protocol EP-17-A4 and with a proportions of false positives less than $5\%$ and false negatives less than $5\%$ , based on 144 determinations, with 80 blank and 64 low level samples; $\mathrm{LoB} = 3.64\mathrm{mg / dL}$ . The LoQ is $10\mathrm{mg / dL}$ glucose, which was determined by assaying a stripped serum pool spiked with $10\mathrm{mg / dL}$ glucose 64 times.
e. Analytical specificity:
Several interfering substances have been identified by assaying spiked serum pools. Significant interference is defined by the sponsor as a shift in results by more than both $4\mathrm{mg / dL}$ and $4\%$ and the below data meets levels of acceptable interference as defined.
| Interferent | Glucose Concentration | Interferent Concentration | Observed Interference |
| --- | --- | --- | --- |
| Ascorbic acid | 75 mg/dL | 30 mg/L | none |
| | 140 mg/dL | | |
| Bilirubin | 90 mg/dL | 4.8 mg/dL | -3.3 mg/dL |
| | 146 mg/dL | 6.4 mg/dL | -3.6% |
| Hemoglobin | 76 mg/dL | 240 mg/dL | -3.6 mg/dL |
| | 139 mg/dL | 160 mg/dL | -3.8% |
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| Lipemia | 72 mg/dL | 600 mg/dL | + 4 mg/dL |
| --- | --- | --- | --- |
| (from Intralipid) | 142 mg/dL | 80 mg/dL | + 3.9% |
| Metronidazole | 76 mg/dL | 24 mg/L | + 2.4 mg/dL |
| | 139 mg/dL | 48 mg/L | + 3.1% |
| Tetracycline | 76 mg/dL | 15 mg/L | none |
| | 141 mg/dL | | |
Bilirubin, hemoglobin, lipemia and metronidazole interfere with this test. This information has been included in the labeling..
f. Assay cut-off:
Not Applicable
2. Comparison studies:
a. Method comparison with predicate device:
173 Serum specimens ranging in glucose concentration from 26 to 496 mg/dL glucose were collected from individual patients and were assayed for glucose using the Carolina Liquid Chemistries Glucose Reagents with the BioLis 24i Analyzer and the predicate device.
y = 0.974x + 2.22, r = 0.999
b. Matrix comparison:
Not Applicable – serum is the only sample type indicated
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:
Reference range for glucose in serum is 74 to 106 mg/dL*
* Burtis CA, Ashwood ER, Bruns DE, editors, Tietz Textbook of Clinical Chemistry and Molecular Diagnostics. Elsevier Inc., St. Louis, MO, 2006.
N. Instrument Name:
Biolis 24i Clinical Chemistry Analyzer
O. System Descriptions:
1. Modes of Operation:
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Does the applicant's device contain the ability to transmit data to a computer, webserver, or mobile device?:
Yes ☐ X or No ☐
Does the applicant's device transmit data to a computer, webserver, or mobile device using wireless transmission?:
Yes ☐ or No ☐ X
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:
Barcode read option
4. Specimen Sampling and Handling:
Direct sample collection tube sampling, routine and stat sampling
5. Calibration:
Various calibration types such as one point, multiple point, rate
6. Quality Control:
Contains built in QC program
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 substantial equivalence decision.
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Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.