Clinically-calibrated Accelerated Fatigue Test for Predicting the Clinical Performance of Dental Restorative Materials - Project Summary/Abstract There is now an urgent need to develop more clinically relevant tests, or medical device development tools (MDDT), that are alternatives to clinical studies to help accelerate the translation of new dental materials. In this biphasic R61/R33 application, we propose a MDDT, in the form of an accelerated fatigue test calibrated by clinical data, for assessing the clinical performance of resin composites. The method explicitly predicts the survival probability of composite restorations as a function of time, through some easy-to-perform cyclic fatigue and biofilm tests on a simple yet clinically representative model composite restoration. Our immediate goal is to have this MDDT qualified by the FDA for use by dental materials manufacturers, while our long-term goal is to extend the method and application of this tool to other medical devices. Our strategy for qualifying the proposed MDDT contains the following specific aims: Phase 1, Aim 1 Confirm repeatability of accelerated fatigue test for model resin-composite restorations. The fatigue test using conventional materials will be repeated multiple times. The resulting survival probability curves are expected to lie within the 95% interval of each other. Phase 1, Aim 2 Assess viability and repeatability of calibrated biofilm model for producing recurrent caries in debonded specimens. Debonded specimens will be challenged using a clinically-calibrated biofilm model. Recurrent caries is expected to be produced consistently in the specimens and the clinical time for it to occur following debonding can be predicted within the required confidence intervals. Phase 2, Aim 3 Determine if laboratory model can accurately predict service life of a wide range of composite restorations using prospective clinical data. Prospective clinical data for different classes of restorations will be collected for calibration and validation of the laboratory model. The calibrated model is expected to be able to accurately predict the clinical performance of different classes of restorations. Phase 2, Aim 4 Determine if laboratory model can accurately predict service life of a wide range of composite restorations using retrospective clinical data. Retrospective clinical data will be collected from the BigMouth Dental Data Repository to further validate the model for life predictions. The recalibrated model is expected to be still capable of accurately predicting the service life of the restorations. Phase 2, Aim 5 Assess viability and repeatability of accelerated fatigue and biofilm tests for assessing resin composites with caries prevention and remineralization properties. Specimens made of materials with or without antibacterial properties will be challenged using the calibrated fatigue and biofilm models. Resin composites with antibacterial agents are expected to take longer to develop recurrent caries, and the results are repeatable.
