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Computational Models for new Patients Stratification Strategies of Neuromuscular Disorders

Project description

Advancing diagnosis for hereditary neuromuscular diseases

The EU-funded CoMPaSS-NMD project creates novel and universal tools for the diagnostic stratification of patients suffering from hereditary neuromuscular diseases (HNMDs) aiming at personalised treatments. HNMDs often strike early in life, causing severe disabilities and significantly reducing life expectancy. These conditions hinder daily functioning, leading to social isolation and the need for constant care. Many patients require long-term institutionalisation, putting strain on both families and healthcare systems. Accurate diagnosis is challenging due to the complexity of these diseases. The CoMPaSS-NMD project, using clinical, genetic, histologic and imaging data from five European countries, applies AI-driven clustering (NMD Atlas Platform) to identify patient subgroups and provide precise clinical characterisation and diagnosis, improving diagnosis and making data accessible to the research community.

Objective

The CoMPaSS-NMD project creates novel and universal tools for the diagnostic stratification of patients suffering from Hereditary NeuroMuscular Diseases (HNMDs) aiming at personalised treatments.
HNMDs often occurs in young people, causing long-term disability and early death; these conditions bring lack of participation, need for permanent assistance and may require long-term institutionalisation.
Multidimensional HNMD data - clinical, genetic, histopathological and MRI will be provided by third-level clinical centers in Italy, France, Germany, Finland and the United Kingdom as part of the European Reference Network for Rare Neurological Diseases. Computational tools for high-dimensional clustering will be applied in an unsupervised learning approach using the internal structure of data to define groups of similar patients. Classification model averaging and integration techniques for federated learning-inspired model building and novel HNMD-specific descriptors of histopathological images will be implemented.
The adoption of this multidimensional view has the potential to increment the diagnostic rate of HNMDs by 30% and foster effective actions by European national health systems.
As main project outcome, the CoMPaSS-NMD Atlas Platform will be a cost-effective AI-based application providing precise clinical characterization and diagnosis, with data remaining publicly available for anyone in the research and health community to use.
The project will deliver Recommendations and Guidelines for stratification-based patient management to offer superior standard-of-care for diagnosis and prognosis and assist in planning clinical trials. It will follow a user-centred, co-design methodology with a strong stakeholder engagement and networking with other project consortia.
The project engages partners with clinical, biotechnological, ICT, AI, ethical and legal, communication and exploitation competences: 6 clinical/academic centres, 1 academic, 4 industrial partners.

Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-HLTH-2022-TOOL-12-two-stage

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Coordinator

UNIVERSITA DEGLI STUDI DI MODENA E REGGIO EMILIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 653 750,00
Address
VIA UNIVERSITA 4
41121 MODENA
Italy

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Region
Nord-Est Emilia-Romagna Modena
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 653 750,00

Participants (9)

Partners (2)

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