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510(k) Data Aggregation

    K Number
    K230035
    Date Cleared
    2023-04-05

    (90 days)

    Product Code
    Regulation Number
    866.2390
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    BioSci™ Disposable Virus Sampling Tubes

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

    BioSci™ Disposable Virus Sampling Tube is intended for the collection and transport of clinical specimens containing viruses or chlamydiae from the collection site to the testing laboratory. The system can be processed using standard clinical laboratory operating procedures for culture of clinical specimens.

    Device Description

    BioSci Disposable Virus Sampling Tube includes a screw-cap tube containing transport medium which is divided into two formats – in kit and tube. The format in kit is supplied in pre-packaged collection sets containing one of the two swab types or both of two swabs types: 1. Minitip (2.5 mm tip) flocking swab with 8 cm breaking point, for nasopharyngeal specimen collection 2. Regular (5 mm tip) flocking swab with 3 cm breaking point, for oropharyngeal specimen collection The screw-cap tube in kit format is pre-filled with 1 or 3 mL of transport medium for safe transportation of biological specimen. The format in tube only contains labeled screw-cap tubes pre-filled with 1 mL, 1.5mL, 2 mL and 3 mL of transport medium.

    AI/ML Overview

    The input provided describes a 510(k) premarket notification for a medical device called "BioSci Disposable Virus Sampling Tube." It outlines the device's intended use, description, comparison with a predicate device, shelf-life stability, and performance data from recovery studies.

    However, the provided text does not contain information typically found in acceptance criteria or a study proving device performance in the context of AI/ML-driven diagnostics, which is what your query implies. The device is a "Transport Culture Medium," a physical product for specimen collection and transport, not a diagnostic algorithm.

    Therefore, I cannot extract the following information from the provided text:

    • A table of acceptance criteria and the reported device performance in the context of diagnostic accuracy.
    • Sample size used for the test set or data provenance for a diagnostic algorithm.
    • Number of experts used to establish ground truth or their qualifications.
    • Adjudication method for a test set.
    • MRMC comparative effectiveness study or effect size.
    • Standalone (algorithm only) performance.
    • Type of ground truth used (expert consensus, pathology, outcomes data) for a diagnostic AI.
    • Sample size for the training set of an AI.
    • How ground truth for the training set was established for an AI.

    The performance data included in the document relates to the recovery of viruses and chlamydiae in the transport medium over time and at different temperatures, which is relevant to the physical device's function, not an AI algorithm's performance.

    Here's what I can extract related to the physical device's performance:

    1. A table of (physical device) performance metrics:

    TestAcceptance Criteria (Implicit from Results)Reported Device Performance
    Shelf-Life Stability (18 months)
    AppearancePackage intact, no leakage; media red, transparent, no color change, turbidity, or precipitation.All lots passed criteria for appearance.
    Net ContentVolume not less than labeled volume.All tubes met criteria for volume content.
    pH ValueWithin 7.3 ± 0.3.All tubes at each time point (1, 3, 9, 12, 15, 18 months) were within 7.3 ± 0.3.
    Recovery Studies (0-48 hours)Change in recovery between 0 and 48 hours within one log difference (+/- 90%)
    Adenovirus (4°C)36% increase
    Cytomegalovirus (4°C)-12% decrease
    Herpes Simplex Virus Type 1 (4°C)17% increase
    Influenza A (4°C)-72% decrease
    Chlamydia pneumoniae (4°C)-7% decrease
    Adenovirus (25°C)47% increase
    Cytomegalovirus (25°C)-57% decrease
    Herpes Simplex Virus Type 1 (25°C)20% increase
    Influenza A (25°C)-90% decrease
    Chlamydia pneumoniae (25°C)-18% decrease

    2. Sample size used for the test set and the data provenance:

    • For shelf-life: Three lots of the BioSci Disposable Virus Sampling Tube were evaluated.
    • For recovery studies: Four lots of media representing newly manufactured and older media were evaluated.
    • Provenance: The studies were conducted by Shenzhen Dakewe Bio-engineering Co., Ltd. (China). The type of study (retrospective or prospective) is not explicitly stated, but performance tests for medical devices are typically prospective evaluations of the device's capabilities.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth here refers to the actual viral/chlamydial titer, measured by standard laboratory methods (Fluorescent Foci Count), not expert opinions on images or clinical data.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.

    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, as this is not an AI/ML device.

    6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable, as this is not an AI/ML device.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

    • For recovery studies: The "ground truth" was the initial infectious particle count (Fluorescent Foci Count) at 0 hours, and subsequent counts were compared against this baseline. This relies on quantitative laboratory assays.
    • For shelf-life stability: Visual inspection (appearance), volume measurement (net content), and pH measurement were used as objective ground truths.

    8. The sample size for the training set: Not applicable, as this is not an AI/ML device.

    9. How the ground truth for the training set was established: Not applicable, as this is not an AI/ML device.

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