# Probabilistic multifactorial lifetime assessment for resin-based composite restorations

> **NIH NIH R01** · UNIVERSITY OF MINNESOTA · 2021 · $406,809

## Abstract

Title: Probabilistic multifactorial lifetime assessment for resin-based composite restorations
Abstract:
While the development of the next-generation dental composites to extend the service life of tomorrow's dental restorations
is underway, producing a rigorous tool that can better discriminate the many composite restorative systems by more
accurately predicting their clinical performances is necessary. The long term goal of this project is to increase the lifetime
of resin-base composite restorations by obtaining more durable restorative systems through a better understanding of the
degradation mechanisms of the tooth-composite interface. Our more immediate goal is to develop a comprehensive and
complementary analytical-experimental approach for predicting the lifetime of composite restorations. We would like to
test the hypotheses that (1) the different mechanical, thermal, chemical and biological challenges work synergistically
to reduce the lifetime of resin-based composite restorations; (2) we can predict the lifetime of composite-restored
teeth using numerical stress analysis and a multi-factorial failure model; and (3) we can devise an accelerated test
method with representative challenges that reproduce the failure rates and failure modes seen in composite-restored
teeth clinically. We propose to conduct a series of laboratory and theoretical studies including 1) to develop and implement
a multifactorial probabilistic model for failure prediction; 2) to determine the material properties pertinent to the failure
model for commercial composites subjected to calibrated representative biomechanical challenges; 3) to predict the lifetime
of different types of composite restorations (Class I and II) for premolars and molars using the failure model and the
interfacial stresses predicted by Finite Element Analysis; 4) to design and build a microbiomechanical artificial mouth
(µBAM) by adding a biofilm reactor to an artificial mouth based on the existing design at the Minnesota Dental Research
Center for Biomaterials and Biomechanics (MDRCBB) to simulate the microbiological and mechanical challenges in the
oral environment; and 5) to develop an accelerated test regime using the multifactorial failure model together with a
continuously increasing load. This research will introduce a comprehensive and quantitative approach to the structural
analysis and lifetime prediction of composite dental restoration, validated by comparison with clinical results. It will assess
degradation of the tooth-restoration interface under representative preparation and oral conditions, and the results will help
elucidate the individual and synergistic effects of two main oral challenges, namely microbiological and biomechanical, and
those of operator error on its lifetime. The project will also produce a microbiomechanical artificial mouth that can test
composite-restored teeth under accelerated but clinically representative conditions, thus reducing the scope and cost...

## Key facts

- **NIH application ID:** 10093010
- **Project number:** 5R01DE027043-03
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Alex Siu-Lun Fok
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $406,809
- **Award type:** 5
- **Project period:** 2019-02-01 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10093010

## Citation

> US National Institutes of Health, RePORTER application 10093010, Probabilistic multifactorial lifetime assessment for resin-based composite restorations (5R01DE027043-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10093010. Licensed CC0.

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