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Translational METabolomics for NEurodegenerative Diseases dIAgnosis and prognosis

Sector: Government • Location: Italy, Cyprus, United Kingdom, Denmark, Greece

Source: EU Funding & Tenders Portal

Project
Ongoing

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

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The project “Translational METabolomics for NEurodegenerative Diseases dIAgnosis and prognosis” is an infrastructure initiative in the Government sector, located in Italy, Cyprus, United Kingdom, Denmark, Greece. Taiyo aggregates data on it from EU Funding & Tenders Portal.

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ongoing

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Description

Description

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.

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Source reliability

High

Data quality score

100%

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