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For storage of soft (hydrophilic), and rigid gas permeable (RGP) hard contact lenses during disinfection with buffered 3% hydrogen peroxide contact lens solution.

The device is a specialized lens case consisting of a transparent cup with a connected unit of screw cap, lens holders (baskets) and platinum-coated neutralization disc. The platinum catalyst coating and shape of the plastic disc are designed to effectively neutralize hydrogen peroxide in the lens care system to harmless water and oxygen gas.

The provided text describes a 510(k) premarket notification for a medical device called "Clear Care Cleaning & Disinfecting Solution, AOCup Lens Case with AODisc." This submission is for a modification to an existing device, specifically a change in the silicone material of a gasket and its coating within the lens case.

The document does not contain the kind of detailed acceptance criteria and study information typically associated with AI/ML-based medical devices or diagnostic tools. Instead, it focuses on the safety and efficacy of a contact lens care product and its components. Therefore, many of the requested fields related to AI/ML study design will not be applicable.

Here's an attempt to answer the questions based on the available information, noting where information is not present:

1. A table of acceptance criteria and the reported device performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify sample sizes for the tests conducted (biocompatibility, physicochemical, and design functionality). It also does not provide details on data provenance beyond indicating the submitter (Alcon Laboratories, Inc., USA, with a contact in Germany) and the FDA's review process. These types of tests are typically bench tests or laboratory assessments of materials, not clinical studies with human subjects or retrospective/prospective data collection in the sense of an AI/ML diagnostic.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This question is not applicable to the scope of this regulatory submission. The "ground truth" here is established by adherence to recognized international standards (ISO, USP, EP) and internal engineering design specifications for material properties and device function. There were no human experts establishing a "ground truth" for a diagnostic outcome.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable. The tests described are laboratory and bench tests, not assessments requiring human adjudication of diagnostic outcomes.

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. This is not an AI/ML device or a diagnostic tool involving human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Not applicable. This is not an AI/ML device.

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

The "ground truth" or reference standards used are:

• International Standards: Subparts of ISO 10993 (for biocompatibility).
• Pharmacopeia Standards: USP (United States Pharmacopeia) and EP (European Pharmacopoeia) requirements (for extractable and leachable testing).
• Engineering Design Specifications: Related to coating adhesion and overall functionality of the gasket within the lens case.

8. The sample size for the training set

Not applicable. This is not an AI/ML device and does not involve a "training set."

9. How the ground truth for the training set was established

Not applicable. This is not an AI/ML device and does not involve a "training set."

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