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510(k) Data Aggregation
(43 days)
For in vitro diagnostic use (i.e. for external use only) by healthcare professionals and in the home by people with diabetes mellitus to assess the performance of the Roche Accu-chek Active, the Bayer Ascensia Microfill, and the LifeScan OneTouch Ultra and FastTake Blood Glucose Monitors.
The Liberty Normal Glucose Control consists of a viscosity-adjusted, aqueous liquid control solution containing a known quantity of glucose. The product is packaged in plastic dropper tipped bottles for easy application of the control solutions to the test strips and a red coloration to aid the user to visually confirm application of the control. The product is non-hazardous and contains no human or animal derived materials.
The provided document describes a Quality Control Material for blood glucose monitors, not an AI/ML-powered diagnostic device. Therefore, many of the requested categories for AI/ML device studies (such as sample size for test sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, training set data, etc.) are not applicable.
The document focuses on demonstrating substantial equivalence to existing predicate devices based on comparable characteristics and performance studies relevant to control solutions.
Here's a breakdown of the available information relevant to acceptance criteria and performance, alongside an explanation of why certain AI/ML-specific questions cannot be answered:
1. Table of Acceptance Criteria and Reported Device Performance
| Characteristic/Aspect | Acceptance Criteria (Implied by Predicate Equivalence) | Reported Device Performance (Liberty Normal Glucose Control) |
|---|---|---|
| Device Type | Single Analyte Control Solution (Glucose) | Single Analyte Control Solution (Glucose) |
| Number of Levels | 1 (matching most predicates) | 1 |
| Analytes | Glucose | Glucose |
| Container | Plastic bottle with dropper-tip | Plastic bottle with dropper-tip |
| Fill Volume | Comparable to predicates (e.g., 2.5 mL - 4 mL range) | 3.6 mL |
| Color | Red (matching most predicates) | Red |
| Matrix | Buffered aqueous solution of D-Glucose, viscosity modifier, preservatives, and other non-reactive ingredients | Buffered aqueous solution of D-Glucose, viscosity modifiers, preservatives, and other non-reactive ingredients |
| Intended Use | To assess performance of specific blood glucose monitors | To assess performance of specific blood glucose monitors (Bayer Ascensia Microfill, Roche Accu-chek Active, LifeScan OneTouch Ultra, and FastTake) |
| Target Population | Professional and home use | Professional and home use |
| Performance Studies | Stability (Accelerated and Real-time), Open Vial, Microbial Stress Stability, Test precision data comparable to predicates | "Tests were performed to verify specific performance characteristics: Stability (Accelerated and Real-time), Open Vial, Microbial Stress Stability, Test precision." (Details not provided in this summary, but concluded to support substantial equivalence). |
Explanation of Applicability/Non-Applicability to AI/ML Questions:
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2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
- Not applicable for a control solution. This device is a consumable quality control material, not a diagnostic algorithm. Performance is assessed through chemical stability and precision testing, not diagnostic accuracy on a patient dataset. The "test set" here would refer to vials of the control solution and measurements taken by various blood glucose meters.
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3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):
- Not applicable. Ground truth for a glucose control solution is established by precise chemical formulation and analytical testing, not by expert interpretation of medical images or patient data.
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4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable. Adjudication methods are relevant for ambiguous diagnostic interpretations, not for the chemical properties and performance of a control solution.
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5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- Not applicable. This pertains to AI-assisted diagnostic reads, which is not what this device is.
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6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. This device is a control solution, not an algorithm.
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7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- Ground truth: For a glucose control solution, the ground truth is the known, precisely manufactured concentration of glucose within the solution, verified through analytical chemistry methods.
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8. The sample size for the training set:
- Not applicable. This device is not an AI/ML algorithm that requires a training set. Its formulation is based on chemical engineering and existing predicate control solutions.
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9. How the ground truth for the training set was established:
- Not applicable. As above, no training set for this type of device.
Conclusion:
The Liberty Normal Glucose Control is a chemical control solution designed to verify the performance of blood glucose monitors. Its acceptance criteria and performance are established through demonstrating substantial equivalence to legally marketed predicate devices by comparing their physical characteristics, chemical matrix, intended use, and through standard performance studies for such products (stability, open vial, microbial stress, and test precision). The 510(k) summary indicates that these comparisons and studies support the claim of substantial equivalence. The document is not for an AI/ML diagnostic device, so questions related to AI/ML specific study designs are not relevant.
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