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510(k) Data Aggregation

    K Number
    K251076
    Date Cleared
    2025-07-30

    (113 days)

    Product Code
    Regulation Number
    878.4810
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K232863

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

    The KALA Therapy Wand (Model: KALA-03) is intended for the treatment of facial wrinkles, and mild to moderate inflammatory acne. The red light is intended for the treatment of wrinkles, and the blue light is intended for the treatment of mild to moderate inflammatory acne.

    Device Description

    The KALA Therapy Wand (Model: KALA-03) is indicated for over-the-counter aesthetic use. The red light is intended for the treatment of wrinkles, and the blue light is intended for the treatment of mild to moderate inflammatory acne. The device is vibrating in red light model. The device is powered by a Lithium-Ion rechargeable battery, and it has a charging cable, USB charging stand, protective goggles, storage case and instruction manual.

    The wand can be rotated 135 degrees in either direction.

    There are two switches of the device: one function is red light to wrinkle removal and vibration for relax, the other function is blue light to treat mild to inflammatory acne.

    The device will automatically shut down after 12 minutes of operation. The recommended treatment time is 3 minutes per area. After every three minutes of treatment, the device will vibrate to indicate the time. If you need to continue treatment, simply turn on the device again.

    AI/ML Overview

    The provided FDA 510(k) clearance letter and summary for the KALA Therapy Wand (Model: KALA-03) primarily focus on demonstrating substantial equivalence to predicate devices through non-clinical testing. This type of clearance generally does not require extensive clinical performance studies with detailed acceptance criteria and human reader studies as would be seen for a new or complex AI/ML-driven diagnostic device.

    Based on the provided information, the device is a light-based therapy device for over-the-counter use, intended for aesthetic purposes (facial wrinkles and mild to moderate inflammatory acne). The "study" proving the device meets acceptance criteria is a non-clinical performance testing approach demonstrating compliance with relevant electrical safety, electromagnetic compatibility, photobiological safety, battery safety, and biocompatibility standards. Software verification and validation, and usability validation were also performed.

    Here's the breakdown of the information requested, as extractable from the provided document:


    Acceptance Criteria and Device Performance

    Since this is a non-clinical submission, the "acceptance criteria" are compliance with established safety and performance standards. There isn't a table of statistical performance metrics, but rather successful adherence to defined technical and safety requirements.

    Table of Acceptance Criteria and Reported Device Performance (Non-Clinical Compliance)

    Acceptance Criteria CategorySpecific Standard/Requirement MetReported Device Performance
    Electrical SafetyIEC 60601-1 (Edition 3.2, 2020-08)Compliant
    IEC 60601-1-11 (Edition 2.1, 2020-07)Compliant
    IEC 60601-2-57 (Edition 1.0, 2011-01)Compliant
    Electromagnetic CompatibilityIEC 60601-1-2 (Edition 4.1, 2020-09)Compliant
    Photobiological SafetyIEC 62471 (First edition, 2006-07)Compliant
    Battery SafetyIEC 62133-2 (Edition 1.0, 2017-02)Compliant
    BiocompatibilityISO 10993-5 (Cytotoxicity)Compliant (based on identical materials to cleared device)
    ISO 10993-10 (Sensitization)Compliant (based on identical materials to cleared device)
    ISO 10993-10 (Irritation)Compliant (based on identical materials to cleared device)
    SoftwareFDA Guidance: "Content of Premarket Submissions for Device Software Functions"Software V&V conducted; classified as Basic Documentation Level.
    UsabilityUser testing for Usability ValidationUsability testing conducted.

    Study Details (as applicable for a non-clinical submission):

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

      • Test Set (Device Testing): The "test set" here refers to the device prototypes/units that underwent the non-clinical tests. The document does not specify the number of units tested for electrical safety, EMC, etc., which is typical for such submissions.
      • Data Provenance: The testing was conducted by or for the manufacturer (Shenzhen Kaiyan Medical Equipment Co., Ltd) in China, as indicated by the submitter's information. It's inherently "prospective" in the sense that the tests were performed on the device designed for submission.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

      • This is a non-clinical submission for a device used for aesthetic purposes. The concept of "ground truth" established by medical experts (like radiologists for image analysis) is not applicable here. The "ground truth" for these tests is defined by the passing criteria of the international standards themselves (e.g., specific thresholds for electrical leakage, EMC emissions, irradiance, etc.). Compliance is assessed by qualified test engineers and labs.
    3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

      • Not applicable. Adjudication methods are typically used in clinical studies, especially those involving subjective assessments or disagreements among human readers. Non-clinical testing against objective standards does not involve expert adjudication in this manner.
    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 study is not relevant for this type of aesthetic, light-based therapy device where the claim is not for assisting human readers in diagnosis. The clearance is based on safety and functional equivalence.
    5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

      • Not applicable. This device is not an algorithm for diagnosis or image analysis. It is a physical device providing light therapy. Its "standalone" performance refers to its ability to meet the specified technical parameters and safety standards.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • The "ground truth" for demonstrating substantial equivalence and safety in this context is compliance with recognized international consensus standards (e.g., IEC, ISO). The performance is measured against these technical specifications, not against clinical outcomes or expert consensus on medical conditions.
    7. The sample size for the training set:

      • Not applicable. This device does not involve a machine learning algorithm that requires a "training set" in the traditional sense of AI/ML software. The software component, as described, is for controlling device functions ("Basic Documentation Level software"), not for learning from data.
    8. How the ground truth for the training set was established:

      • Not applicable, as there is no training set for an AI/ML algorithm.
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