AI-PARKNET
L’Ente Capofila del progetto è Fondazione IRCCS Istituto Neurologico Casimiro Mondino. Il Responsabile Scientifico del progetto è la Professoressa Enza Maria Valente.
| Patologia: | Parkinson |
| Area Tematica: | Intelligenza Artificiale |
| Data di Inizio Progetto: | 01.04.2026 |
| Data di Fine Progetto: | 31.03.2029 |
| Finanziamento: | € 2.000.000,00 |
| Partenariato | Fondazione IRCCS Istituto Neurologico Casimiro Mondino Fondazione IRCCS Istituto Neurologico Carlo Besta Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico Politecnico di Milano |
Parkinson disease (PD) has a lifetime risk of 3-4% with a constantly increasing prevalence. No preventive strategies are available and, despite intense research, treatment remains symptomatic. It is emerging that PD does not represent a single entity but rather encompasses distinct clinical, physiopathological and genetic subtypes. The growing number of failed attempts to establish disease-modifying therapies for PD is likely due to an inadequate selection of participants, often centered on a clinical-driven approach.
Artificial Intelligence (AI) techniques hold the potential to identify novel homogeneous clusters of PD patients through the integration of large sets of multimodal data, collected from multiple centers and properly harmonized. We propose to develop an integrated system for collection, curation, harmonization and AI-based analysis of multimodal data based in Regione Lombardia. We will feed this system with clinical, genomics, proteomics, biochemical and neuroimaging data from a large cohort of PD patients and prodromal subjects followed-up for at least 4 years. Through multiple state-of-the-art AI-based analyses, we aim to unravel distinct biologically homogeneous subtypes of PD, which offer the potential to enable personalized strategies for management and treatment. As a second aim, we will make this system interoperable and easily accessible to multiple centers, providing an essential set-up for data collection and analysis of additional prospective cohorts.