The GLP systems Track is a modular laboratory automation system designed to automate pre-analytical and post-analytical processing, including sample handling, in order to automate sample processing in clinical laboratories. The system consolidates multiple analytical instruments into a unified workflow. The Alinity c System is a fully automated, random/continuous access, clinical chemistry analyzer intended for the in vitro determination of analytes in body fluids. The Alinity c ICT (Integrated Chip Technology) is used for the quantitation of sodium, potassium, and chloride in human serum, plasma, or urine on the Alinity c 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
Modular laboratory automation system (LAS) for clinical labs; automates pre- and post-analytical sample processing; inputs include patient sample tubes (primary/secondary); performs barcode identification, centrifugation, decapping, aliquoting, recapping, and storage; transports samples via carriers identified by Near-Field Communication (NFC) tags; interfaces with Alinity c-series analyzers; communicates sample ID and test orders; enables automated sample delivery to analyzers; reduces manual handling; improves workflow efficiency; healthcare providers use analyzer-generated results for diagnosis/monitoring of electrolyte/metabolic disorders.
Clinical Evidence
No clinical data. Bench testing only, including design verification, software and hardware verification, design validation, chain of custody testing for sample ID, method comparison study (automated vs. manual), electromagnetic compatibility, and electrical safety testing.
Technological Characteristics
Modular laboratory automation system; utilizes NFC tags for sample carrier identification; includes touchscreen user interfaces; integrates with Alinity c-series analyzers; electrical safety per IEC 61010-1, IEC 61010-2-081, IEC 61010-2-101; EMC compliance per EN/IEC 61326-2-6; battery safety per UL 1642, UL 2054, IEC 62133-2.
Indications for Use
Indicated for use in clinical laboratories to automate pre- and post-analytical sample processing (handling, centrifugation, decapping, aliquoting, recapping, storage) for patients requiring electrolyte (sodium, potassium, chloride) testing in serum, plasma, or urine.
Regulatory Classification
Identification
A sodium test system is a device intended to measure sodium in serum, plasma, and urine. Measurements obtained by this device 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.
Predicate Devices
ACCELERATOR APS (k093318)
Submission Summary (Full Text)
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FDA
U.S. FOOD & DRUG
ADMINISTRATION
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
ASSAY AND INSTRUMENT
## I Background Information:
A 510(k) Number
k213486
B Applicant
Abbott Laboratories
C Proprietary and Established Names
GLP systems Track
D Regulatory Information
| Product Code(s) | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| JGS | Class II | 21 CFR 862.1665 - Sodium Test System | CH - Clinical Chemistry |
| CEM | Class II | 21 CFR 862.1600 - Potassium test system | CH - Clinical Chemistry |
| CGZ | Class II | 21 CFR 862.1170 - Chloride test system | CH - Clinical Chemistry |
| JJE | Class I | 21 CFR 862.2160 - Discrete photometric chemistry analyzer for clinical use | CH - Clinical Chemistry |
| JQP | Class I | 21 CFR 862.2100 - Calculator/data processing module for clinical use | CH - Clinical Chemistry |
## II Submission/Device Overview:
A Purpose for Submission:
The submission is to obtain clearance for the GLP systems Track, a laboratory automation system used with clinical laboratory analyzers such as the Alinity c System.
Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993-0002
www.fda.gov
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The manufacturer uses the performance of Sodium, Potassium, and Chloride assays within the Alinity c ICT Sample Diluent to demonstrate the GLP systems Track barcode sample ID transmission to the analyzer and analytical equivalence to manual sample introduction versus automated sample introduction on the analyzer.
**B Measurand:**
Sodium, Potassium, Chloride
**C Type of Test:**
Quantitative, potentiometric
**III Intended Use/Indications for Use:**
**A Intended Use(s):**
See Indications for Use below.
**B Indication(s) for Use:**
The GLP systems Track is a modular laboratory automation system designed to automate pre-analytical and post-analytical processing, including sample handling, in order to automate sample processing in clinical laboratories. The system consolidates multiple analytical instruments into a unified workflow.
The Alinity c System is a fully automated, random/continuous access, clinical chemistry analyzer intended for the in vitro determination of analytes in body fluids.
The Alinity c ICT (Integrated Chip Technology) is used for the quantitation of sodium, potassium, and chloride in human serum, plasma, or urine on the Alinity c 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.
**C Special Conditions for Use Statement(s):**
Rx - For Prescription Use Only
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D Special Instrument Requirements:
Alinity c System
IV Device/System Characteristics:
A Device Description:
The GLP systems Track is a modular laboratory automation system (LAS) used to perform multiple pre-analytical and post-analytical steps to automate sample preparation and distribution processes in clinical laboratories. These processes include bar code identification of samples, centrifugation, aliquoting of samples, decapping of samples, transport of samples between processes (modules), delivery of samples to Abbott Alinity c-series laboratory analyzers, capping of samples, and storage of samples. The GLP systems Track consists of the track, modules, and specific analyzer interfaces used to connect analyzers and the control system. Each module includes a built-in touchscreen, a user interface that functions as a central operating and display element. Due to the modular nature of the LAS, customers may select modules and configurations to fit their laboratory needs.
B Principle of Operation:
Ion-selective electrodes (ISE) for sodium, potassium, and chloride utilize membranes selective to each of these ions. An electrical potential (voltage) is developed across the membranes between the reference and measuring electrodes in accordance with the Nernst equation. The voltage is compared to previously determined calibrator voltages and converted into ion concentration.
C Instrument Description Information:
1. Instrument Name:
GLP systems Track
2. Specimen Identification:
Barcode identification of patient samples. GLP systems Track reads sample bar codes and electronically communicates sample identification number to the analyzers.
3. Specimen Sampling and Handling:
The patient's sample tubes are loaded onto the GLP systems Track Input/Output Module (IOM) or BulkLoader Module to be centrifuged, de-capped, aliquoted, recapped and stored. The sample bar codes are read to direct the sample to a specific analyzer.
4. Calibration:
Provided in k170320 (Alinity c ICT Sample Diluent)
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5. Quality Control:
Provided in k170320 (Alinity c ICT Sample Diluent)
This medical device product has functions subject to FDA premarket review as well as functions that are not subject to FDA premarket review. For this application, if the product has functions that are not subject to FDA premarket review, FDA assessed those functions only to the extent that they either could adversely impact the safety and effectiveness of the functions subject to FDA premarket review or they are included as a labeled positive impact that was considered in the assessment of the functions subject to FDA premarket review.
V Substantial Equivalence Information:
A Predicate Device Name(s):
ACCELERATOR APS
B Predicate 510(k) Number(s):
k093318
C Comparison with Predicate(s):
| Device & Predicate Device(s): | k213486 | k093318 |
| --- | --- | --- |
| Device Trade Name | GLP systems Track | ACCELERATOR APS |
| | | |
| Intended Use/Indications For Use | Modular laboratory automation system designed to automate pre-analytical and post-analytical processing, including sample handling, in order to automate sample processing in clinical laboratories. | Same |
| Principle of Analyte Detection | An analyzer’s detection method remains the same when interfaced to the subject device. | Same |
| Sample Containers | Primary tubes and secondary aliquot tubes. | Same |
| Sample Aspiration | Directly from tube presented to the aspiration point by the subject device. | Same |
| Sample Pre-Analytics | Centrifugation: | Same |
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K213486 - Page 5 of 9
| Device & Predicate Device(s): | k213486 | k093318 |
| --- | --- | --- |
| | GLP systems Track automatically centrifuges sample tubes. Samples may also be manually centrifuged by lab personnel prior to loading into the system.
**Decapping:**
GLP systems Track automatically decaps sample tubes. Samples may also be manually decapped by lab personnel prior to loading into the system.
**Aliquoting:**
GLP systems Track automatically aliquots samples from the primary sample to bar coded secondary tubes.
**Recapping/Resealing:**
GLP systems Track automatically recaps sample tubes. Samples may also be manually recapped/ resealed by lab personnel prior to loading into system.
**Storage:**
GLP systems Track automatically stores sample tubes in temperature-controlled storage. Samples may also be returned to IOM for lab personnel to manually store samples in lab. | |
| Sample Identification | GLP systems Track reads sample bar codes and electronically communicates sample ID to analyzers. The analyzer reads sample bar codes for samples loaded directly onto the analyzer or for samples transferred in a rack to the analyzer from the LAS. | Same |
| Test Orders | Unidirectional from Laboratory Information System or | Same |
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| Device & Predicate Device(s): | k213486 | k093318 |
| --- | --- | --- |
| | middleware to the analyzer. | |
| Test Results | Unidirectional from Laboratory Information System or middleware from the analyzer. | Same |
| LAS Communication | GLP systems Track communicates to the analyzer per each analyzer's LAS interface specification. | Same |
| General Device Characteristic Differences | | |
| Sample Loading | GLP systems Track Input/Output Module (IOM) accepts samples loaded into sample racks. The BulkLoader Module accepts samples loaded into the bin. Samples may also be loaded directly into any analyzers that support local sample loading. | ACCELERATOR APS IOM accepts samples loaded into sample racks. Samples may also be loaded directly into any analyzers that support local sample loading. |
| Sample Transport | GLP systems Track transports sample CARs identified on the system by Near-Field Communication (NFC) tags. Samples may also be manually transported by lab personnel to analyzers. | ACCELERATOR APS transports sample carriers identified on the system by Radio Frequency identification (RFID) tags. Samples may also be manually transported by lab personnel to analyzers. |
VI Standards/Guidance Documents Referenced:
AAMI ANSI BP22:2011 Blood Pressure Transducers (Section 4, p. 32)
UL 1642 5th Edition – Lithium Batteries (Section 17, p. 17-3)
UL 2054 2nd Edition – Household and Commercial Batteries (Section 17, p. 17-3)
IEC 62133-2 Edition 1.0 2017-02 – Secondary cells and batteries containing alkaline or other non-acid electrolytes – Safety requirements (Section 17, p. 17-3)
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IEC 61010-1:2010 AMD1:2016 Safety Requirements for Electrical Equipment for Measurement, Control, and Laboratory Use - Part 1: General Requirements
IEC 61010-2-081:2019 - Safety requirements for electrical equipment for measurement, control and laboratory use - Part 2-081: Particular requirements for automatic and semi-automatic laboratory equipment for analysis and other purposes
IEC 61010-2-101:2018 - Safety requirements for electrical equipment for measurement, control and laboratory use - Part 2-101: Particular requirements for in vitro diagnostic (IVD) medical equipment
EN 61326-2-6:2013 and IEC 61326-2-6: 2020 Electrical equipment for measurement, control and laboratory use EMC requirements – Part 2-6: Particular requirements – In vitro diagnostic (IVD) medical equipment and collateral standards.
CLSI EP09c Measurement Procedure Comparison and Bias Estimation Using Patient Samples. 3rd Edition
## VII Performance Characteristics (if/when applicable):
### A Analytical Performance:
1. **Precision/Reproducibility:**
Provided in k170320 (Alinity c ICT Sample Diluent)
2. **Linearity:**
Provided in k170320 (Alinity c ICT Sample Diluent)
3. **Analytical Specificity/Interference:**
Provided in k170320 (Alinity c ICT Sample Diluent)
4. **Assay Reportable Range:**
Provided in k170320 (Alinity c ICT Sample Diluent)
5. **Traceability, Stability, Expected Values (Controls, Calibrators, or Methods):**
Provided in k170320 (Alinity c ICT Sample Diluent)
6. **Detection Limit:**
Provided in k170320 (Alinity c ICT Sample Diluent)
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7. Assay Cut-Off:
Not applicable
8. Accuracy (Instrument):
Provided in k170320 (Alinity c ICT Sample Diluent)
9. Carry-Over:
Not applicable
## B Comparison Studies:
1. Method Comparison with Predicate Device:
A method comparison study was performed based on recommendations in CLSI EP09c.
The method comparison study was performed to demonstrate equivalence between results for samples processed using the GLP systems Track and delivered to the Alinity c analyzer (investigational method) and samples directly loaded on the Alinity c analyzer by the operator (comparator method).
A total of 100 human serum and plasma samples (50 of each specimen type) were obtained. The samples were tested for sodium, potassium, and chloride. A subset of samples were contrived, (either spiked with chemicals containing sodium, potassium, or chloride or diluted with deionized water) to obtain samples with concentrations at the upper end/lower end of the measuring interval of the assays.
For the investigational and comparator method, the samples were tested using one lot of reagent, two lots of calibrator, and one lot of controls. For the investigational method samples were tested using one GLP systems Track SAL Alinity c-series module and processed using one Alinity c analyzer. For the comparator method, the samples were tested using one Alinity c analyzer. Each sample was tested in singlicate using both methods.
Only samples with results that were within the respective measuring interval for both methods were included in the analysis. A Passing-Bablok evaluation was performed using all samples by comparing the result from the investigational method versus the result from the comparator method. The regression analysis results for each assay and specimen type are summarized in the table below:
| Analyte | N | Sample Range (mmol/L) | Slope | Intercept | Correlation Coefficient (r) |
| --- | --- | --- | --- | --- | --- |
| Sodium Plasma | 50 | 104.6-192.3 | 0.99 | 2.3 | 1.00 |
| Sodium Serum | 50 | 106.7-189.9 | 0.99 | 1.2 | 1.00 |
| Potassium Plasma | 50 | 1.1-9.6 | 1.00 | 0.0 | 1.00 |
| Potassium Serum | 50 | 1.1-9.5 | 1.00 | 0.0 | 1.00 |
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| Analyte | N | Sample Range (mmol/L) | Slope | Intercept | Correlation Coefficient (r) |
| --- | --- | --- | --- | --- | --- |
| Chloride Plasma | 50 | 50.8-144.2 | 0.99 | 1.8 | 1.00 |
| Chloride Serum | 50 | 51.8-139.8 | 1.00 | 0.3 | 1.00 |
2. Matrix Comparison:
Not applicable
C Clinical Studies:
1. Clinical Sensitivity:
Not applicable
2. Clinical Specificity:
Not applicable
3. Other Clinical Supportive Data (When 1. and 2. Are Not Applicable):
Not applicable
D Clinical Cut-Off:
Not applicable
E Expected Values/Reference Range:
Provided in k170320 (Alinity c ICT Sample Diluent)
F Other Supportive Instrument Performance Characteristics Data:
Not applicable
VIII Proposed Labeling:
The labeling supports the finding of substantial equivalence for this device.
IX 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.