K112408 · Polymedco, Inc. · CEM · Nov 4, 2011 · Clinical Chemistry
Device Facts
Record ID
K112408
Device Name
POLY-CHEM 90 ISE MODULE
Applicant
Polymedco, Inc.
Product Code
CEM · Clinical Chemistry
Decision Date
Nov 4, 2011
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 862.1600
Device Class
Class 2
Indications for Use
The Poly-Chem 90 ISE Module is for the quantitative in vitro measurement of sodium, potassium, and chloride in human serum on the Poly-Chem 90 clinical chemistry analyzer. Sodium measurements are used in the diagnosis and treatment of aldosteronism (excessive secretion of the hormone aldosterone), diabetes insipidus (chronic excretion of large amounts of dilute urine, accompanied by extreme thirst), adrenal hypertension, Addison's disease (caused by destruction of the adrenal glands), dehydration, inappropriate antidiuretic hormone secretion, or other diseases involving electrolyte imbalance. Potassium measurements are used to monitor electrolyte balance in the diagnosis and treatment of diseases conditions characterized by low or high blood potassium levels. Chloride measurements are used in the diagnosis and treatment of electrolyte and metabolic disorders such as cystic fibrosis and diabetic acidosis.
Device Story
Poly-Chem 90 ISE Module is an ion-selective electrode (ISE) accessory for the Poly-Chem 90 clinical chemistry analyzer; performs quantitative in vitro measurement of sodium, potassium, and chloride in human serum. Device utilizes ISE technology to measure ion concentrations; results are displayed on the analyzer interface for use by clinicians to diagnose and monitor electrolyte and metabolic disorders. System is intended for professional use in clinical laboratory settings. Benefits include rapid, accurate electrolyte quantification to support clinical decision-making for conditions such as cystic fibrosis, diabetic acidosis, and adrenal dysfunction.
Clinical Evidence
No clinical data. Performance established via bench testing, including precision (10-day study, two instruments), linearity, and analytical specificity (interference testing for hemoglobin, bilirubin, and triglyceride). Method comparison against predicate device (n=63-74 samples) showed high correlation (r=0.9929-0.9985) and acceptable bias. All testing followed CLSI guidelines (EP05-A2, EP06-A, EP17-A).
Technological Characteristics
Ion-selective electrode (ISE) technology; quantitative measurement of sodium, potassium, and chloride; utilizes Medica Calibrator A and B; standalone module integrated into Poly-Chem 90 clinical chemistry analyzer; serum sample input.
Indications for Use
Indicated for quantitative in vitro measurement of sodium, potassium, and chloride in human serum for patients requiring electrolyte assessment, including those with suspected aldosteronism, diabetes insipidus, adrenal hypertension, Addison's disease, dehydration, electrolyte/metabolic disorders, cystic fibrosis, or diabetic acidosis.
Regulatory Classification
Identification
A potassium test system is a device intended to measure potassium in serum, plasma, and urine. Measurements obtained by this device are used to monitor electrolyte balance in the diagnosis and treatment of diseases conditions characterized by low or high blood potassium levels.
Predicate Devices
Randox RX Daytona ISE Module (k024014)
Submission Summary (Full Text)
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510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
ASSAY AND INSTRUMENT COMBINATION TEMPLATE
A. 510(k) Number:
k112408
B. Purpose for Submission:
New 510(k) for the addition of an Ion Selective Electrode Module for the previously cleared Poly-Chem 90 analyzer (k090703)
C. Measurand:
Sodium, Potassium, Chloride
D. Type of Test:
Quantitative Ion Selective Electrodes (ISE)
E. Applicant:
POLYMEDCO, INC.
F. Proprietary and Established Names:
POLY-CHEM 90 ISE MODULE
G. Regulatory Information:
1. Regulation section:
21CFR Sec.-862.1600-Potassium test system.
21CFR Sec.-862.1170-Chloride test system.
21CFR Sec.-862.1665-Sodium test system.
2. Classification:
II
3. Product code:
CEM - Electrode, Ion Specific, Potassium
CGZ - Electrode, Ion-Specific, Chloride
JGS - Electrode, Ion Specific, Sodium
4. Panel:
Chemistry (75)
H. Intended Use:
1. Intended use(s):
See Indication(s) for use below
2. Indication(s) for use:
The Poly-Chem 90 ISE Module is for the quantitative in vitro measurement of
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sodium, potassium, and chloride in human serum on the Poly-Chem 90 clinical chemistry analyzer.
Sodium measurements are used in the diagnosis and treatment of aldosteronism (excessive secretion of the hormone aldosterone), diabetes insipidus (chronic excretion of large amounts of dilute urine, accompanied by extreme thirst), adrenal hypertension, Addison's disease (caused by destruction of the adrenal glands), dehydration, inappropriate antidiuretic hormone secretion, or other diseases involving electrolyte imbalance.
Potassium measurements are used to monitor electrolyte balance in the diagnosis and treatment of diseases conditions characterized by low or high blood potassium levels.
Chloride measurements are used in the diagnosis and treatment of electrolyte and metabolic disorders such as cystic fibrosis and diabetic acidosis.
3. Special conditions for use statement(s):
Prescription use
4. Special instrument requirements:
POLY-CHEM 90 analyzer (k090703) and ISE module
I. Device Description:
The POLY-CHEM 90 ISE module is integrated on the Poly-Chem 90, a bench-top fully automated random access clinical analyzer. The analyzer has the capacity to perform up to 90 tests per hour plus ISEs, and offers primary tube sampling, on-board sample dilution and a cooled reagent compartment.
J. Substantial Equivalence Information:
1. Predicate device name(s):
Randox RX Daytona ISE Module
2. Predicate 510(k) number(s):
k024014
3. Comparison with predicate:
| Similarities and Differences ISE Module | | |
| --- | --- | --- |
| Item | Poly-Chem 90 ISE Module | RX Daytona ISE Module |
| Intended Use /Indications for Use | For the quantitative in vitro measurement of the level of sodium, potassium, and chloride. Sodium measurements are used in the diagnosis and treatment of aldosteronism (excessive secretion of the hormone aldosterone), diabetes insipidus (chronic excretion of large amounts of dilute urine, accompanied | Same |
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| Similarities and Differences ISE Module | | |
| --- | --- | --- |
| Item | Poly-Chem 90 ISE Module | RX Daytona ISE Module |
| | by extreme thirst), adrenal hypertension, Addison's disease (caused by destruction of the adrenal glands), dehydration, inappropriate antidiuretic hormone secretion, or other diseases involving electrolyte imbalance. Potassium measurements are used to monitor electrolyte balance in the diagnosis and treatment of diseases conditions characterized by low or high blood potassium levels. Chloride measurements are used in the diagnosis and treatment of electrolyte and metabolic disorders such as cystic fibrosis and diabetic acidosis. | |
| Analyzer | Poly-Chem 90 analyzer. | RX Daytona analyzer. |
| Sample type | Serum | Serum, plasma, urine |
| Methodology | Ion selective electrode | Same |
| Calibration | Medica Calibrator A and Calibrator B | Same |
| Analyzer | Poly-Chem 90 | RX Daytona |
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 - Protocols for Determination of Limits of Detection and Limits of Quantitation - EP17-A
- ISO 14971:2007, Medical devices - Application of risk management to medical devices.
L. Test Principle:
ISE measurements are based on the potentiometric Nernst Equation principle. The measured potential difference between the reference electrode and the ion specific electrodes is proportional to the logarithm of the concentration of the measured ions.
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
a. Precision/Reproducibility:
Precision studies were performed at three levels of each test, on two separate instruments, over 10 days. Serum samples were tested in duplicate twice a day.
| | | | | Within run | | Between run | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | Sample | Instrument | Mean (mmol/L) | SD | CV | SD | CV |
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| | | | | Within run | | Between run | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | Sample | Instrument | Mean (mmol/L) | SD | CV | SD | CV |
| Sodium | 1 | 1 | 83.54 | 0.222 | 0.27 | 0.781 | 0.94 |
| | | 2 | 82.91 | 0.101 | 0.12 | 0.589 | 0.71 |
| | 2 | 1 | 139.05 | 0.254 | 0.18 | 0.783 | 0.56 |
| | | 2 | 139.70 | 0.160 | 0.11 | 0.646 | 0.46 |
| | 3 | 1 | 172.03 | 0.285 | 0.17 | 0.768 | 0.45 |
| | | 2 | 172.95 | 0.099 | 0.06 | 0.481 | 0.28 |
| | | | | Within run | | Between run | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | Sample | Instrument | Mean (mmol/L) | SD | CV | SD | CV |
| Potassium | 1 | 1 | 2.43 | 0.008 | 0.33 | 0.026 | 1.08 |
| | | 2 | 2.41 | 0.007 | 0.29 | 0.022 | 0.90 |
| | 2 | 1 | 3.91 | 0.007 | 0.18 | 0.019 | 0.49 |
| | | 2 | 3.89 | 0.007 | 0.17 | 0.017 | 0.43 |
| | 3 | 1 | 7.3 | 0.012 | 0.16 | 0.046 | 0.63 |
| | | 2 | 7.3 | 0.010 | 0.14 | 0.049 | 0.68 |
| Chloride | 1 | 1 | 54.4 | 0.29 | 0.54 | 0.66 | 1.20 |
| | | 2 | 53.8 | 0.17 | 0.32 | 0.53 | 0.98 |
| | 2 | 1 | 101.0 | 0.15 | 0.14 | 0.35 | 0.34 |
| | | 2 | 101.0 | 0.08 | 0.08 | 0.37 | 0.36 |
| | 3 | 1 | 134.0 | 0.15 | 0.11 | 0.45 | 0.34 |
| | | 2 | 133.8 | 0.13 | 0.10 | 0.44 | 0.33 |
# b. Linearity/assay reportable range:
Reportable range based on linearity and detection limit below:
33.5 - 191.6 mmol/L (Na)
1.09 - 9.98 mmol/L (K)
41.0 - 169.8 mmol/L (Cl)
Dilution series for the assay was prepared by mixing human serum with human serum containing the analyte to several levels of the test. The diluted samples were tested in triplicate on the Poly-Chem 90 analyzer.
The mean of the measured concentration at each level was compared with the expected concentration based on the dilution level and the linear fit was assessed. The linearity claim is based on a percent deviation of $< 10\%$ through the linear range.
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| | Range (mmol/L) | Slope (95% CI) | Intercept (95% CI) | r² |
| --- | --- | --- | --- | --- |
| Sodium | 30.4 – 191.6 | 0.99 (0.97 to 1.00) | 0.09 (-1.92 to 2.11) | 0.9989 |
| Potassium | 1.09 – 9.98 | 0.98 (0.98 to 0.99) | 0.17 (0.13 to 0.21) | 0.9998 |
| Chloride | 31.3 – 169.8 | 1.02 (1.00 to 1.04) | -5.35 (-7.62 to -3.07) | 0.9989 |
c. Traceability, Stability, Expected values (controls, calibrators, or methods): The calibrators, electrodes, and wash buffer used with the Poly-Chem 90 ISE are cleared under k000926
c. Detection limit:
The below limits of detecting was established according to CLSI - Protocols for Determination of Limits of Detection and Limits of Quantitation - EP17-A.
| Test | Limit of Blank | Limit of Detection | Limit of Quantitation (10% CV) |
| --- | --- | --- | --- |
| Sodium | 32.4 mmol/L | 33.5 mmol/L | 33.5 mmol/L |
| Potassium | 0.35 mmol/L | 0.393 mmol/L | 0.5 mmol/L |
| Chloride | 40.2 mmol/L | 41.0 mmol/L | 41.0 mmol/L |
d. Analytical specificity:
Serum samples containing the analyte at three levels of the test were spiked with the potentially interfering substance—hemoglobin, bilirubin, and triglyceride—to several concentrations. Samples were then run in triplicate using the Poly-Chem 90 test. The recovery of the test at each concentration of interferent was calculated by comparing the mean result of testing with no interferent to the mean result at each level tested. Acceptable recovery at each level was 90 – 110%.
| Test | Hemoglobin | Bilirubin | Triglyceride |
| --- | --- | --- | --- |
| Sodium | 800 mg/dL | 7.5 mg/dL | 549 mg/dL |
| Potassium | 800 mg/dL | 25 mg/dL | 663 mg/dL |
| Chloride | 800 mg/dL | 25 mg/dL | 549 mg/dL |
f. Assay cut-off: Not Applicable
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2. Comparison studies:
a. Method comparison with predicate device:
Patient serum samples (some adjusted) at several levels of the test were run on the RX Daytona instrument and the Poly-Chem 90. Results obtained from each instrument were compared using Passing-Bablok and Bland Altman analysis. Results are summarized in the table below:
| Test | n | Range of samples | Slope (95% CI) | Intercept (95% CI) | r |
| --- | --- | --- | --- | --- | --- |
| Sodium | 63 | 56.0 – 189.0 | 1.04
(1.00 to 1.08) | -5.06
(-11.47 to -0.30) | 0.9929 |
| Potassium | 74 | 1.39 – 9.13 | 0.99
(0.97 to 1.01) | 0.02
(-0.04 to 0.11) | 0.9982 |
| Chloride | 74 | 49.0 – 166.0 | 1.01
(1.00 to 1.03) | -1.64
(-2.91 to -0.10) | 0.9985 |
b. Matrix comparison:
Not Applicable
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*:
Sodium (serum) 136 – 146 mmol/L
Potassium (serum) 3.5 – 5.1 mmol/L
Chloride (serum) 97 – 107 mmol/L
* Todd-Sanford, clinical Diagnosis by Laboratory Methods, (16th edition) W.B. Saunders Co., Philadelphia, P.A. 144-148.
N. Instrument Name:
POLY-CHEM 90 analyzer with ISE module
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:
Manual or barcode entry with optional barcode reader
4. Specimen Sampling and Handling:
Removable tray with sample tube holder on a turntable. On-board sampling dilution capability
5. Calibration:
ISE (reference electrode)
6. Quality Control:
Use of quality control materials are recommended for daily runs.
P. Other Supportive Instrument Performance Characteristics Data Not Covered In The "Performance Characteristics" Section above:
Not Applicable
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.
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.