Project description
Metabolomic analysis and AI-based diagnostic tool for neurodegenerative diseases
The prevalence of neurodegenerative disorders such as Alzheimer’s, Parkinson’s, and ALS is closely linked to increased life expectancy. Diagnosis is challenging due to overlapping symptoms, misinterpretation of early signs, and wide variability in patient presentation. Supported by the Marie Skłodowska-Curie Actions programme, the METNEDIA project aims to develop a new diagnostic tool for neurodegenerative conditions using metabolomic analysis and AI. Untargeted metabolomic approaches will first be used to identify key biomarkers. Based on these findings, the project will design a diagnostic kit combining mass spectrometry with AI across multiple centres. It will also assess the in vitro neurotoxic effects of relevant molecules. Bioinformatics and machine learning will help uncover the biological mechanisms driving these disorders.
Objective
The prevalence of neurodegenerative disorders, including Alzheimer’s disease, Parkinson’s disease, Amyotrophic lateral sclerosis and frontotemporal dementia, continues to rise, partly due to increasing life expectancy. The diagnosis of these disorders remains a significant challenge due to overlapping symptoms, delayed recognition of early symptoms often mistaken for normal aging, and variability in symptom presentation across patients.
METNEDIA will tackle these challenges by proposing a new framework for the development of a diagnostic tool. METNEDIA will utilize metabolomic analysis and artificial intelligence to develop a diagnostic tool for the diagnosis of neurodegenerative diseases. A discovery phase will be initially performed using untargeted metabolomic approaches to identify most relevant biomarkers. The project will then develop of a diagnostic kit based on mass spectrometry and artificial intelligence for the diagnosis of widely diffuse neurodegenerative diseases. A multicenter validation of the kit will be also performed. Neurotoxic evaluation of molecules identified as relevant for each disease will be evaluated in vitro. Finally, bioinformatic and machine learning will be used to gaining insight on the biology of neurodegenerative disorders using in vitro and in vivo data.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-SE - HORIZON TMA MSCA Staff Exchanges
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-SE-01
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13100 Vercelli
Italy
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