CoMPaSS-NMD - Computational Models for New Patients Stratification Strategies of HNMD

Condition(s) studied

Investigational drug(s) / intervention(s)

AI-guided patient classification: The intervention consist in firstly obtaining clinical, genetic, histopathological, MRI data from total 500 patients coming from the defined Cohorts. The adaptative AI-tool developed, based on data provided, will then identify multi-modal characteristics that will support patients' superclusters and their multi-omics signatures.

Study summary

The project "Computational Models for new Patients Stratification Strategies of Neuromuscular Disorders" (CoMPaSS-NMD) creates novel and universal tools for the diagnostic stratification of patients suffering from Hereditary Neuromuscular Diseases (HNMDs) aiming at personalised treatments. HNMDs often occur in young people, causing long-term disability and early death; these conditions bring lack of participation in society, 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 AI-based application providing precise clinical characterization of patients. 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: six clinical/academic centres, one academic, and four industrial partners.

Eligibility

Primary outcome measure(s)

• Updated database of patients with HNMD that will be used to validate the algorithms and computational models developed in the unsupervised studies of existing genetic, histopathological, and MRI data — 36 months
  * number of newly diagnosed HNMD patients assigned to a particular supercluster-based phenotype category (+30%); * number of patients' superclusters and their multi-omics signatures achieved (at least 6); * digital representations of the data from total 500 patients included in the study.

Trial sites (3)

More University of Modena and Reggio Emilia trials in Italy