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510(k) Data Aggregation

    K Number
    K052074
    Date Cleared
    2005-09-01

    (31 days)

    Product Code
    Regulation Number
    886.5918
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    JSZ-STAT-TREE, AND JSZ-STAT-OR, CLEANING, DISINFECTING AND STORING SOLUTIONS; JSZ-WET-TREE AND JSZ-WET-OR

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

    JSZ-Stat-Tree Cleaning, Disinfecting, Storage Solution is indicated for use in the cleaning, chemical disinfection and storage of fluoro/silicone acrylate and silicone acrylate (RGP) contact lenses.

    JSZ-Stat-Or Cleaning, Disinfecting, Storage Solution is indicated for use in the cleaning, chemical disinfection and storage of fluoro/silicone acrylate and silicone acrylate (RGP) contact lenses.

    JSZ-Wet-Tree Wetting. Lubricating, Rewetting Drops are indicated for use to wet fluoro/silicone acrylate and silicone acrylate rigid gas permeable (RGP) contact lenses prior to lens insertion and to rewet and lubricate the lens while on the eye.

    JSZ-Wet-Or Wetting. Lubricating, Rewetting Drops are indicated for use to wet fluoro/silicone acrylate and silicone acrylate rigid gas permeable (RGP) contact lenses prior to lens insertion and to rewet and lubricate the lens while on the eye.

    Device Description

    Cleaning, Disinfecting and Storing Solutions; and Wetting, Lubricating and Rewetting Solutions for Rigid Gas Permeable Contact Lenses.

    AI/ML Overview
    1. Table of Acceptance Criteria and Reported Device Performance:

      The document does not explicitly present a table of acceptance criteria with quantified performance metrics to be considered "met" in the traditional sense for a medical device. Instead, the approach taken for these contact lens solutions is a demonstration of substantial equivalence to existing legally marketed predicate devices. The "performance" is implicitly deemed acceptable if the new products exhibit comparable chemical, toxicological, and microbiological characteristics to the predicates.

      Test CategoryAcceptance Criteria (Implied)Reported Device Performance
      ChemistryCompatibility with RGP lenses; effective daily cleanerJSZ-Stat-Tree/JSZ-Wet-Tree and JSZ-Stat-Or/JSZ-Wet-Or systems were compatible with all groups of RGP lenses. Both JSZ-Stat-Tree and JSZ-Stat-Or were shown to be effective daily cleaners.
      ToxicologyComparable to or passing established safety tests for predicates- Cytotoxicity: NA (cleaning solutions), Passed (wetting solutions)
    • Acute Oral Toxicity: Passed
    • Ocular Irritation (21d rabbit): Passed
    • Ocular Irritation (72hr rabbit): Passed
    • Anesthetic Effect: NA (cleaning solutions), Passed (wetting solutions)
    • Guinea Pig Maximization: Passed
    • Corneal Epithelial Wound Healing: Passed
    • Corneal Penetration: Passed |
      | Microbiology | Acceptable disinfection efficacy, neutralizer efficacy, preservative efficacy, and sterility/stability | - Disinfection Efficacy: Passed (JSZ-Stat-Tree, JSZ-Stat-Or), NA (wetting solutions)
    • Neutralizer Efficacy: Passed (JSZ-Stat-Tree, JSZ-Stat-Or), NA (wetting solutions)
    • Preservative Efficacy: Passed (all products)
    • Sterility/Stability: Passed (all products) |
      | Clinical Studies | Not required if formulations are identical to previously approved devices | No clinical data included; explicitly stated "Clinical data is not required for solutions using the same active ingredients at the same concentrations as currently marketed products." |
      | Substantial Equivalence | Identical to or substantially equivalent to predicate devices with similar formulations and indications | Solutions are identical to DeStat-3, DeStat-4, Stay-Wet 3, and Stay-Wet-4 solutions; substantially equivalent to Optimum by Lobob and Claris Cleaning and Soaking Solution. |
    1. Sample size used for the test set and the data provenance:
      The document does not specify discrete "test sets" in the context of a typical clinical study. The toxicology and microbiology tests were likely conducted on laboratory samples of the solutions themselves, not on human subjects or clinical data sets. The provenance of the data is from laboratory testing of the JSZ products, and comparisons to legally marketed predicate devices in the US market. The study is not a clinical study; it's a pre-market notification (510(k)) relying on substantial equivalence to existing products, with supportive lab data.

    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
      Not applicable (N/A). This submission relies on laboratory testing and comparison to predicate devices, not on expert consensus for a "ground truth" in the diagnostic sense. The regulatory body (FDA) reviews the submitted data.

    3. Adjudication method for the test set:
      N/A. There was no clinical test set requiring adjudication in the context of this 510(k) submission.

    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:
      N/A. This is a submission for contact lens solutions, not an AI-powered diagnostic device. No MRMC study was performed.

    5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
      N/A. This is not an algorithm or AI device. The "performance" refers to the solutions' chemical, toxicological, and microbiological properties.

    6. The type of ground truth used:
      The "ground truth" for demonstrating safety and effectiveness relies on established scientific methods for toxicology (e.g., rabbit ocular irritation, acute oral toxicity) and microbiology (e.g., disinfection efficacy, preservative efficacy), as well as the prior regulatory acceptance of chemically identical or substantially equivalent predicate devices. There is no single "ground truth" in the context of pathology or outcomes data as would be found in a diagnostic study.

    7. The sample size for the training set:
      N/A. There is no "training set" in the context of an AI/ML algorithm or a traditional clinical trial here. The submission is based on laboratory tests of the formulated solutions.

    8. How the ground truth for the training set was established:
      N/A. As there is no training set for an AI/ML model, there is no ground truth established for such a set.

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