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510(k) Data Aggregation

    K Number
    K123397
    Date Cleared
    2013-01-31

    (87 days)

    Product Code
    Regulation Number
    872.3690
    Panel
    Dental
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Multilink Automix is used for the permanent cementation of indirect restorations where a strong bond is desired:

    • Inlays, onlays, crowns, bridges and root posts made of: –
      • o Metal and metal ceramics
      • o All-ceramics, in particular opaque zirconium oxide ceramics
      • o Composites and fibre-reinforced composites
    Device Description

    Multilink Automix is a self-curing and self-etching luting composite system for the adhesive luting of indirect restorations made of metalceramic all-ceramic and composite. Multilink Automix is applied together with the selfetching and self-Ocuring Multilink Primer. Monobond Plus is recommended as a coupling agent to achieve a strong bond to precious and non-precious alloys, as well as to all ceramics made of zirconium and aluminum oxide and silicate ceramics.

    AI/ML Overview

    The provided text describes the submission for MULTILINK AUTOMIX to the FDA for 510(k) clearance. The focus of the study is to demonstrate substantial equivalence to a predicate device, not necessarily to set new, absolute acceptance criteria for the new device as a standalone product based on clinical outcomes.

    Here's a breakdown of the requested information based on the provided document:

    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria are implicitly defined by the performance of the predicate device, Multilink (K032470), as the new device, Multilink Automix, aims to show substantial equivalence. The "acceptance criteria" for the Multilink Automix are therefore that its performance falls within an expected range relative to the predicate, demonstrating it is "substantially equivalent" and "no new issues of safety and effectiveness" persist.

    PropertyUOMPredicate Device (Multilink K032470)Multilink Automix (Self Curing) Reported PerformanceMultilink Automix (Dual Curing) Reported PerformanceAcceptance Criteria (Implied: Substantially Equivalent to Predicate)
    Working time (37C)Min3-43-4--Within range of 3-4 min
    Setting timeMin7-96-7--Within a comparable range to 7-9 min
    Film Thicknessµm<20<50<50<50 µm (Note: Higher than predicate, but still acceptable for this class of device)
    Water Absorptionµg/mm³<25.0<40<40<40 µg/mm³ (Note: Higher than predicate, but acceptable)
    Water solubilityµg/mm³<3.0<7.5<7.5<7.5 µg/mm³ (Note: Higher than predicate, but acceptable)
    Radiopacity%Al350350350350 %Al (Matches predicate)
    Flexural StrengthMPa90±1070±20110±10Comparable to 90±10 MPa (Self-curing slightly lower, dual-curing higher, but both within a reasonable range for equivalence)
    Modulus of ElasticityMPa5000±10003250±4006000±400Comparable to 5000±1000 MPa (Ranges overlap sufficiently)
    Compressive StrengthMPa250±20240±20280±20Comparable to 250±20 MPa (Ranges overlap sufficiently)
    TransparencyBase (trans and Cat)Yellow and CatOpaque and Cat%12±1.510±1.52±0.512±1.510±1.52±0.512±1.510±1.52±0.5Matches predicate values
    Vickers HardnessMPa370--440±30Comparable to 370 MPa (Dual-curing is higher, which is generally positive)
    Shear Bond StrengthDentin / 24hEnamel/ 24hMPa21±223+417±518+321±223+4Comparable to 21±2 and 23+4 MPa (Dual-curing matches, self-curing slightly lower but potentially acceptable)

    Note: The acceptance criteria are "implied" because the document focuses on demonstrating substantial equivalence to the predicate device, meaning the new device's performance should be within an acceptable range of the predicate's performance.

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

    The document does not explicitly state the sample sizes for each specific test (e.g., number of specimens for flexural strength tests). It only indicates that "The device was tested in accordance with ISO 4049:2000" and other standards. These standards typically specify minimum sample sizes for material property tests.

    The data provenance is from Ivoclar Vivadent, Inc., which is listed as being in Amherst, NY, USA. The data is from laboratory testing performed to demonstrate material properties, and thus is considered prospective in the sense that the tests were conducted specifically for this submission, although not on live patients.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

    This type of information is not applicable to this submission. The "ground truth" here is objective physical and chemical properties of a dental material, measured using standardized laboratory methods (e.g., ISO 4049:2000). It does not involve expert interpretation or clinical assessment by medical professionals to establish a truth.

    4. Adjudication Method for the Test Set

    This is not applicable. As explained above, the "truth" is established by laboratory measurement, not by expert consensus or adjudication.

    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

    This is not applicable. This submission is for a dental material/device (luting composite system), not an AI-powered diagnostic or imaging device that would involve human readers or AI assistance.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    This is not applicable. This is a dental material, not an algorithm.

    7. The Type of Ground Truth Used

    The "ground truth" for the performance data presented is derived from standardized laboratory testing and measurements of material properties (e.g., Water Absorption, Flexural Strength, Shear Bond Strength) as per ISO 4049:2000 and other relevant standards.

    8. The Sample Size for the Training Set

    This is not applicable. This submission is for a physical dental material, not a machine learning model that requires a training set.

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

    This is not applicable for the same reason as above.

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