Big data: 6 centers together to improve the management and treatment of central nervous system diseases
PRESS RELEASE by IRCCS San Martino Polyclinic Hospital/APSS and FBK
Sharing clinical data in a structured way so as to improve the ability to predict, prevent and treat conditions such as Alzheimer’s and Parkinson’s disease, ALS, multiple sclerosis and brain tumors, reducing their impact on the national health system. This is the objective of the NeuroArt P3 project, led by the IRCCS Policlinico San Martino Hospital and co-funded by the Ministry of Health and the Regional Governments of the partner centers.
Genoa, November 17, 2020 – The three-year program coordinated by the IRCCS Policlinico San Martino Hospital kicked off, that involves the Gaslini Children’s Hospital and the University of Genoa, Fondazione Bruno Kessler and the Trento Province Healthcare System, in collaboration with TrentinoSalute4.0 (Competence Center on Digital Health), the Neuroradiology Unit of the IRCCS San Raffaele Hospital in Milan and the Don Gnocchi Hospital in Florence. The project aims to optimize the use of the huge amount of clinical data and improve the management of diseases of the central nervous system, collect the highest possible number of epidemiological, clinical and laboratory information (BIG DATA) to process, through artificial intelligence techniques, mathematical algorithms to the end of identifying patterns of disease prognosis and response to therapies.
Big data represents one of the most delicate nodes for healthcare organizations: clinical information is constantly growing, especially for chronic and multifactorial diseases, comes from multiple sources and is often encoded and stored in different formats and media.
To be used to their full potential, it requires rapid processing, a uniform architecture as well as digital platforms and specific mathematical and clinical skills.
“We share the intent of the Ministry of Health to standardize the amount of clinical and laboratory data that is available in our Centers when it comes to neurological diseases, such as Alzheimer’s disease, Parkinson’s disease, ALS, Multiple Sclerosis and brain tumors. Thanks to current digital technologies, we can process information with greater accuracy and obtain indications to guide intervention strategies and research areas”, Antonio Uccelli, Scientific Director of the San Martino Polyclinic, Full Professor at the University of Genoa and coordinator of the network program, said.
The project obtained 2,400,000 euros, half from the Ministry of Health and the other half from the Liguria, Lombardy, Tuscany and Trento Regional Governments.
NeuroArt P3 will therefore start by digitizing, standardizing and organizing the data of patients with central nervous system diseases from the clinical centers involved in the study.
The ultimate goal is to develop predictive models and algorithms that will link the health status to the subsequent evolution of such complex diseases, for an increasingly personalized treatment: a challenge that opens up new perspectives for the treatment of neurological diseases.
As for the work involving the researchers at Fondazione Bruno Kessler, in particular with the eHealth research unit, they are as follows:
- construction of a retrospective and prospective shared database of clinical, imaging and laboratory data of patients from the hospitals involved in the project;
- processing of this clinical data to develop different predictive models based on artificial intelligence, able to predict various clinical outcomes regarding neuroinflammatory, neurodegenerative and neuro-oncological diseases (such as Parkinson’s disease, Multiple Sclerosis, Alzheimer’s disease, pediatric and adult brain tumors)
Once developed and validated, the models will strongly push the development of highly innovative procedures and new knowledge useful for improving the opportunities for prevention, diagnosis, treatment, rehabilitation through clinical studies and trials.
[WATCH] the video interview with FBK’s eHealth Unit researcher, Venet Osmani, in charge of the scientific part concerning artificial intelligence and predictive models of the NeuroArt P3 project.Share on Facebook Share on Twitter Share on Pinterest