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510(k) Data Aggregation

    K Number
    K994017
    Date Cleared
    2000-01-27

    (62 days)

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

    ONTRAK TESTCUP 5 M2K, CAT. 11 1850 1

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

    OnTrak TesTcup®5 M2K is an in vitro test intended for professional use for the qualitative detection of drug or drug metabolite in urine. OnTrak TesTcup-5 M2K simultaneously tests for the presence of multiple drugs or drug metabolites.

    The OnTrak TesTcup-5 M2K profile (cutoff) consists of amphetamines (1000 ng/mL), cocaine metabolite (300 ng/mL), THC (50 ng/mL), morphine (2000 ng/mL) and PCP (25 ng/mL).

    OnTrak TesTcup-5 M2K provides only a preliminary analytical test result. A more specific alternate chemical method must be used in order to obtain a confirmed analytical result. Gas Chromatography/mass spectrometry (GC/MS) is the preferred confirmation method. Clinical consideration and professional judgment should be applied to any drug abuse result, particularly when preliminary positive results are used.

    Device Description

    The OnTrak TesTcup-5 M2K is an in vitro test intended for professional use in the qualitative detection of amphetamines (1000ng/mL), cocaine metabolite (300 ng/mL), THC (50 ng/mL), morphine (2000 ng/mL) and PCP (25 ng/mL).

    The TesTcup assays are based on the principle of microparticle capture inhibition. The test relies on the competition between drug, which may be present in the urine being tested, and drug conjugate immobilized on a membrane in the test chamber.

    Urine is collected directly in the OnTrak TesTcup-5 M2K. After closing the cap and moving it to the “TEST” position, the sample reservoir is filled by tilting the cup. Urine then flows through a membrane by capillary action and reacts with antibody-coated microparticles and drug conjugate present on the membrane. In the absence of drug, the antibody is free to interact with the drug conjugate, causing the formation of a blue band (“negative” sign).

    When drug is present in the specimen, it binds to the antibody-coated microparticles. If sufficient drug is present, the microparticles are inhibited from binding the drug conjugate, and no blue band is formed. A positive sample causes the membrane to remain white (“positive” sign).

    An additional antibody/antigen reaction occurs at the “TEST VALID” area for all assays. The “TEST VALID” blue band forms when antibodies, which are imbedded in the membrane, interact with, and bind to, the antigen on the blue-dyed microparticles.

    AI/ML Overview

    Here's an analysis of the acceptance criteria and study details for the OnTrak TesTcup-5 M2K device, based on the provided text:

    Acceptance Criteria and Device Performance

    Acceptance CriteriaReported Device Performance (OnTrak TesTcup-5 M2K New PCP Monoclonal Antibody)
    PCP Cutoff25 ng/mL
    Precision>95% confidence at 150% cutoff
    PCP Performance: Accuracy (Positive)100% (90 out of 90 PCP positive samples detected)
    PCP Performance: Accuracy (Negative)100% (307 out of 307 PCP negative samples detected)
    Overall Agreement with Abuscreen OnLine for PCP100% (397 samples tested with both devices)

    Study Details

    1. Sample sizes used for the test set and the data provenance:

      • PCP Positive Samples: 90 samples
      • PCP Negative Samples: 307 samples
      • Total Samples for Agreement with Abuscreen OnLine: 397 samples
      • Data Provenance: The negative urine samples were obtained from a clinical laboratory. Positive samples were screened by an automated immunoassay and confirmed positive by GC/MS. The text does not explicitly state the country of origin, but given the submission is to the FDA, it is likely US-based or intended for the US market. The studies appear to be retrospective as they involve predefined sets of samples.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

      • The document does not specify the number or qualifications of experts used to establish the ground truth.
      • For positive samples, the ground truth was established by GC/MS confirmation.
      • For negative samples, the ground truth was established by screening negative by an automated immunoassay.
    3. Adjudication method for the test set:

      • The document does not mention an adjudication method. The ground truth was established by GC/MS or automated immunoassay screening.
    4. 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 an in vitro diagnostic test that provides a qualitative result (color change), not an AI-powered diagnostic image analysis tool requiring human reader interpretation. Therefore, the concept of human readers improving with AI assistance is not applicable here.
    5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

      • Yes, a standalone performance study was done. The device, OnTrak TesTcup-5 M2K, directly provides the result (presence or absence of blue band) based on its chemical reactions, without human interpretation for the result itself. The results obtained from the device were then compared to the ground truth (GC/MS or automated immunoassay).
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • For PCP Positive samples: Confirmed positive by GC/MS.
      • For PCP Negative samples: Screened negative by an automated immunoassay.
      • This is a form of reference method (GC/MS) and established screening method (automated immunoassay).
    7. The sample size for the training set:

      • The document does not explicitly mention a "training set" or its sample size. For an in vitro diagnostic device like this, the development process typically involves internal validation and optimization, rather than a distinct "training set" in the machine learning sense. The performance data presented are for the evaluation/test set.
    8. How the ground truth for the training set was established:

      • Since no explicit training set is mentioned in the context of machine learning, this question is not directly applicable. For the device's development and internal validation, it's reasonable to infer that various concentrations of drugs and control samples would have been used, with their concentrations verified by established analytical methods such as GC/MS.
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