Project description
Advancing dental implant health through microbiome analysis
Dental implant surgeries are on the rise. However, these implants are vulnerable to microbiome-biofilm-associated diseases, which can lead to peri-implantitis, a severe infection resulting in implant loss. We currently lack tools for assessing disease severity. PreBiomics, whose precision medicine test characterises the microbial composition of the plaque biofilm around the implant, has identified specific bacteria that can predict infection severity and progression. The EU-funded PreBiomicsPMT project will develop a test using metagenomics and an artificial intelligence algorithm to enable monitoring, diagnosis and treatment recommendations for patients, based on the bacterial composition of their plaque microbiome. The project will also automate the workflow, working towards a database for developing an antibiotic resistance panel and a decision support system for dentists.
Objective
About 20M dental implants are performed globally per year. Implant market, valued at €3.6B in 2020, is growing at a CAGR of 11%. Unfortunately, microbiome-biofilm-associated diseases can affect dental implants, compromising oral and systemic health. More than 50% of implant patients develop mucositis, an inflammation of the soft tissues, which may lead to peri-implantitis, a severe infection affecting soft and hard tissues that can lead to implant loss. Currently, there are no reliable tools to assess disease severity and risk of disease progression; and the dentist can only prescribe empirical therapies without knowing the composition of the triggering peri-implant plaque microbiome. At PreBiomics, we developed a precision-medicine test that characterises the microbial composition of the plaque biofilm collected in the area surrounding the implant. In 10 years of research, we have shown that specific bacteria's presence is key to predicting the infection's severity and progression. PreBiomicsPMT will develop a test using metagenomics, and an AI algorithm, which will enable the implementation of monitoring and diagnosis and provide treatment recommendations for each patient based on the bacterial composition of their plaque microbiome. Based on the results of the ERC POCs PB3P, this EIC-Transition project aims at automating the workflow using a robotic solution to reduce the costs of the service and speed up the results, building an extensive database that will be used to create an antibiotic resistance panel and further develop our decision support system (DSS) for dentists, finally, conducting a validation study to prove the predictive power of our DSS. Alongside the technical development, we will define the IPR management plan to protect the knowledge we continuously generate, study in-depth the dental implants market and the needs and expectations of our customers and investors and elaborate a robust business plan to allow proper exploitation of our product.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdatabases
- medical and health sciencesclinical medicineodontologydental implantology
- natural sciencesbiological sciencesmicrobiologybacteriology
- medical and health sciencesmedical biotechnologyimplants
- medical and health sciencesbasic medicinepharmacology and pharmacydrug resistanceantibiotic resistance
Keywords
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Funding Scheme
HORIZON-EIC - HORIZON EIC GrantsCoordinator
38123 TRENTO
Italy
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.