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510(k) Data Aggregation

    K Number
    K011672
    Date Cleared
    2001-07-31

    (62 days)

    Product Code
    Regulation Number
    862.3610
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    ACON MAMP ONE STEP METHAMPHETAMINE TEST STRIP, ACON MAMP ONE STEP METHAMPHETAMINE TEST DEVICE

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The ACON mAMP One Step Methamphetamine Test Strip and ACON mAMP One Step Methamphetamine Test Device are rapid chromatographic immunoassays for the qualitative detection of methamphetamine in human urine at a cut-off concentration of 1,000 ng/mL. It is intended for professional and point of care use.

    Device Description

    The ACON mAMP One Step Methamphetamine Test Strip and ACON mAMP One Step Methamphetamine Test Device are competitive binding, lateral-flow immunochromatographic assays for the qualitative detection of methamphetamine in a urine specimen. The test utilizes a mouse monoclonal antibody to selectively detect elevated levels of methamphetamine in urine at a cut-off concentration of 1,000 ng/mL. These tests can be performed and interpreted without the use of an instrument. A drug-positive urine specimen will not generate a colored line in the test region, while a negative urine specimen will generate a colored line in the test region. To serve as procedural control, a colored line will always appear at the control region indicating that a proper volume of specimen has been applied and membrane wicking has occurred. When performing these ACON mAMP tests, one colored line indicates a positive result and two colored lines indicate a negative result; and the test includes a positive results when there is no colored line in the control region.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and study details for the ACON mAMP One Step Methamphetamine Test Strip and Device, based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria are not explicitly stated as distinct targets in the document. However, the study aims to demonstrate substantial equivalence to a predicate device and agreement with GC/MS analysis. Therefore, we can infer the performance metrics from the reported results.

    Metric (Inferred Acceptance Criteria)ACON mAMP One Step Methamphetamine Test StripACON mAMP One Step Methamphetamine Test Device
    Compared to LifeSign Status DS™ MET One-Step Methamphetamine Test
    Positive Agreement (for substantial equivalence)98% (94% - 100% 95% CI)99% (96% - 100% 95% CI)
    Negative Agreement (for substantial equivalence)100% (98% - 100% 95% CI)100% (98% - 100% 95% CI)
    Overall Agreement (for substantial equivalence)99% (97% - 100% 95% CI)100% (98% - 100% 95% CI)
    Compared to GC/MS Analysis Data
    Positive agreement with GC/MS99% (96% - 100% 95% CI)99% (96% - 100% 95% CI)
    Negative agreement with GC/MS94% (89% - 97% 95% CI)93% (86% - 96% 95% CI)
    Total agreement with GC/MS96% (94% - 100% 95% CI)96% (93% - 98% 95% CI)
    Positive Predictive Value (+)93% (88% - 97% 95% CI)92% (86% - 96% 95% CI)
    Negative Predictive Value (-)99% (96% - 100% 95% CI)99% (96% - 100% 95% CI)
    Cut-off Concentration1,000 ng/mL1,000 ng/mL

    2. Sample Size Used for the Test Set and Data Provenance

    • Sample Size for Test Set: 300 urine specimens.
    • Data Provenance: Not explicitly stated, but clinical evaluations are typically conducted with prospective or retrospectively collected real-world samples. The document does not specify the country of origin.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

    The document does not specify the number of experts or their qualifications for establishing the ground truth.

    4. Adjudication Method for the Test Set

    The document does not describe an adjudication method. The reference standard, Gas Chromatography/Mass Spectrometry (GC/MS), is a definitive analytical method, so a separate adjudication process for subjective expert interpretation would likely not be necessary.

    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

    No, an MRMC comparative effectiveness study was not done. This device is a rapid diagnostic test for methamphetamine detection in urine, primarily relying on immunoassay technology for a qualitative result, not an AI-assisted diagnostic tool that would involve human readers interpreting complex images or data with or without AI assistance.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    Yes, a standalone performance evaluation was done. The "ACON mAMP One Step Methamphetamine Test Strip" and "ACON mAMP One Step Methamphetamine Test Device" are themselves the standalone "algorithm" (immunochromatographic assay). Their performance was compared directly to Gas Chromatography/Mass Spectrometry (GC/MS) analysis data, which represents a standalone evaluation of the device's accuracy without a human "interpretation" component beyond reading the visible lines.

    7. The Type of Ground Truth Used

    The ground truth used was Gas Chromatography/Mass Spectrometry (GC/MS) analysis results. GC/MS is a highly accurate and definitive analytical method for identifying and quantifying substances in a sample, making it a reliable "gold standard" for drug detection.

    8. The Sample Size for the Training Set

    The document does not explicitly mention a separate "training set" or its sample size. For an immunochromatographic test, the development process typically involves optimizing reagents and conditions rather than training a machine learning model on a distinct dataset. The "clinical evaluation" described is the test set for performance assessment.

    9. How the Ground Truth for the Training Set Was Established

    Since a distinct training set (in the machine learning sense) is not mentioned for this type of device, the concept of establishing ground truth for a training set is not applicable here. The device's underlying principles are based on antigen-antibody interactions, and its "training" or optimization would involve laboratory development and calibration, using known concentrations of methamphetamine and reference standards, rather than a data-driven ground truth establishment for a training set.

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