(15 days)
Calibrator for Automated Systems (C.f.a.s.) is for use in the calibration of quantitative Roche methods on Roche clinical chemistry analyzers as specified in the enclosed value sheet.
The Calibrator for Automated Systems (C.f.a.s.) is a lyophilized human serum calibrator with chemical additives and materials of biological origin. The concentration of the calibrator components have been adjusted to ensure optimal calibration of the appropriate Roche methods on clinical chemistry analyzers.
1. Acceptance Criteria and Reported Device Performance:
This document is a 510(k) summary for a calibrator device, not a diagnostic or screening device that would have performance metrics like sensitivity, specificity, or accuracy compared to a ground truth diagnosis. Therefore, there are no acceptance criteria in terms of clinical performance metrics like those typically seen for AI-enabled diagnostic tools.
Instead, the "acceptance criteria" for a calibrator device like the Calibrator for Automated Systems (C.f.a.s.) would revolve around its ability to function effectively as a calibrator for Roche clinical chemistry analyzers. This means demonstrating:
- Substantial Equivalence: The primary "acceptance criterion" for a 510(k) submission is to demonstrate substantial equivalence to a legally marketed predicate device. This implies that the new device is as safe and effective as the predicate.
- Accuracy and Precision in Calibration: While not explicitly detailed as "acceptance criteria" within this summary, the underlying studies performed to support substantial equivalence would have involved assessing the calibrator's ability to produce accurate and precise calibration curves and subsequent accurate analyte measurements when used with the specified Roche methods and analyzers. This would typically involve comparing the results obtained using the new calibrator to those obtained using the predicate calibrator, or to established reference materials.
- Stability: Ensuring the calibrator maintains its established values over its shelf-life.
- Traceability: Ensuring the calibrator's values are traceable to higher-order reference materials, if applicable.
Reported Device Performance:
The document explicitly states: "We claim substantial equivalence to the currently marketed Calibrator for Predicate Device Automated Systems (C.f.a.s.) (K990460)." This is the primary reported "performance" from a regulatory standpoint. The FDA's letter (Page 2) confirms: "We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent...".
Therefore, a table of acceptance criteria and performance as typically requested for AI devices is not applicable here. The implicit "acceptance criterion" is successful demonstration of substantial equivalence, and the "performance" is that this was achieved.
2. Sample Size Used for the Test Set and Data Provenance:
This information is not provided in the given 510(k) summary. For a calibrator, the "test set" would likely refer to the number of assays, instruments, and calibrator lots evaluated as part of the validation studies to demonstrate substantial equivalence. The document does not specify these details or the provenance of any data.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:
This concept is not applicable to a calibrator device. Calibrators are used to establish a known relationship between an instrument's signal and an analyte concentration. "Ground truth" for a calibrator's values typically comes from:
- Reference Methods/Materials: Assaying the calibrator against highly accurate reference methods or certified reference materials with established values.
- Gravimetric/Volumetric Preparation: In some cases, values might be assigned based on the precise preparation of the calibrator components.
Experts are not involved in "establishing ground truth" in the way they would for medical image interpretation or clinical diagnosis.
4. Adjudication Method for the Test Set:
This concept is not applicable to a calibrator device. Adjudication methods (like 2+1, 3+1) are used to resolve disagreements among human experts when establishing a clinical ground truth, particularly in diagnostic studies. For a calibrator, the "ground truth" for its values is determined by analytical methods, not human interpretation requiring adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:
No, an MRMC comparative effectiveness study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance for diagnostic tasks, which is not the function of a calibrator.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:
Not applicable in the typical sense of AI algorithms. A calibrator is a physical reagent used in conjunction with an automated instrument. Its "performance" is inherent to its formulation and stability, and its effect is observed when the instrument uses it to generate a calibration curve. There isn't a standalone "algorithm" in the way AI devices have one. The "algorithm" here is the instrument's software interpreting the calibrator's signal to establish the calibration curve. The testing would focus on the accuracy of this curve when using the c.f.a.s.
7. The Type of Ground Truth Used:
For a calibrator, the "ground truth" for its assigned values would typically be:
- Reference Method Values: The concentrations of the analytes in the calibrator are determined using highly accurate and precise reference methods.
- Traceable Standards: The values are often traceable to international or national certified reference materials.
The given document does not explicitly state how the ground truth values for the C.f.a.s. calibrator were established, but these are the standard methods for such devices.
8. The Sample Size for the Training Set:
This concept is not applicable to a calibrator device. Calibrators are reagents, not machine learning models that require a "training set" in the computational sense. The "training" for a calibrator happens in its manufacturing and characterization to ensure its specified values are accurate and stable.
9. How the Ground Truth for the Training Set Was Established:
This concept is not applicable for the same reasons as point 8.
§ 862.1150 Calibrator.
(a)
Identification. A calibrator is a device intended for medical purposes for use in a test system to establish points of reference that are used in the determination of values in the measurement of substances in human specimens. (See also § 862.2 in this part.)(b)
Classification. Class II (special controls). The device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.