Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K243404
    Date Cleared
    2025-07-18

    (259 days)

    Product Code
    Regulation Number
    880.5440
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    HyHub™ and HyHub™ Duo Vial Access Devices

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

    HYHUB™ and HYHUB™ Duo vial access devices are indicated for patients 17 years of age or older to allow a drug to be transferred from vials without using a needle, as prescribed, in a home environment or clinical setting.

    Device Description

    The HYHUB™ and HYHUB™ DUO vial access devices (VAD) are a stand-alone, single-use, disposable, non-pyrogenic, gamma sterilized device, which are intended to support the infusion of two medicinal liquids, as prescribed, in a home environment or clinical setting. The VAD is designed to accommodate up to two (2) or four (4) dual vial units (DVU) to be docked onto the VAD infusion tray which allows the transfer of medicinal liquids in a sequential, needleless manner using standard connections for syringes, applicable pumps, and infusion sets.

    AI/ML Overview

    The FDA 510(k) clearance letter for the HyHub™ and HyHub™ Duo Vial Access Devices (K243404) does not contain the level of detail typically found in a clinical study report or a summary of clinical performance for AI/ML-based devices. Instead, it focuses on demonstrating substantial equivalence to a predicate device through bench testing, biocompatibility testing, and a comparison of technological characteristics.

    Therefore, many of the requested categories relating to acceptance criteria for AI inference, dedicated test sets, expert adjudication, MRMC studies, standalone algorithm performance, and detailed training data are not applicable or cannot be extracted from this document. The document describes a medical device, not an AI/ML algorithm.

    However, I can extract the information relevant to the performance testing that was conducted to demonstrate this device meets its requirements for substantial equivalence.


    1. Table of Acceptance Criteria and Reported Device Performance

    For a traditional medical device like the HyHub, "acceptance criteria" are generally tied to meeting specific performance standards based on recognized test methods or internal protocols. The document does not explicitly state numerical acceptance criteria for each test alongside performance data in a single table, but it lists the tests performed and implies successful completion for substantial equivalence.

    Since the document does not provide specific numerical acceptance criteria and reported performance results for each test (e.g., maximum allowable leak rate vs. measured leak rate), I can only present the categories of tests performed.

    Acceptance Criteria Category (Bench Test)Reported Device Performance (Summary Statement)
    Leak testPerformed successfully, demonstrating the device functions as intended.
    Particulate testPerformed successfully, demonstrating the device functions as intended.
    Luer connectors compatibilityPerformed successfully, demonstrating the device functions as intended.
    Stopper fragmentation testPerformed successfully, demonstrating the device functions as intended.
    Sterile packaging testPerformed successfully, demonstrating the device functions as intended.
    Flow testPerformed successfully (supported pump compatibility, intended use).
    Residual/Injectable Volume testPerformed successfully (supported pump compatibility, intended use).
    Human Factors ValidationPerformed successfully, demonstrating the device functions as intended.

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

    This information is not provided in the FDA 510(k) letter. The document mentions "bench tests" and "biocompatibility evaluation," implying a set of physical devices were tested rather than a "test set" of data in the AI/ML context. No details on the number of units tested per bench test are given, nor is information on geographical origin or retrospective/prospective nature of data for this type of hardware device.


    3. Number of Experts Used to Establish Ground Truth and Qualifications

    This information is not applicable for this type of device and submission. The "ground truth" for a vial access device is its physical performance against established engineering and biocompatibility standards, not expert interpretation of medical images or data.


    4. Adjudication Method

    Not applicable for this device type. Adjudication methods like 2+1 or 3+1 are used in studies involving human interpretation or labeling of data, typically for AI/ML device validation.


    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    No. An MRMC study is not mentioned because this device is a physical vial access device, not an AI/ML diagnostic or assistive tool for human readers.


    6. Standalone Performance Study (Algorithm Only)

    No. This is a physical device, not an algorithm.


    7. Type of Ground Truth Used

    The "ground truth" for this device's evaluation is based on established engineering and biocompatibility standards, and physical performance measurements.

    • Bench Testing: Objective measurements against documented specifications for leak rates, particulate generation, flow rates, residual volumes, connector compatibility, and package integrity.
    • Biocompatibility Testing: Results from established in-vitro and in-vivo tests (e.g., cytotoxicity, sensitization, systemic toxicity, hemolysis) against defined biological safety endpoints as per ISO 10993-1.
    • Sterility Validation: Demonstration of a Sterility Assurance Level (SAL) of 10-6 in accordance with ISO 11137 (for gamma radiation) or ISO 11135 (for ethylene oxide).
    • Pyrogenicity: Testing to confirm the device is non-pyrogenic.

    8. Sample Size for the Training Set

    Not applicable. This is a physical medical device, not an AI/ML algorithm that requires a "training set" of data.


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

    Not applicable, as there is no "training set" for this device.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1