Il Progetto “Digital Driven Diagnostics, prognosis and therapeutics for sustainable Health care”, in sigla “D3 4 Health”, ha per oggetto la realizzazione di interventi compresi nel quadro di attuazione del Piano complementare al Piano Nazionale di Ripresa e Resilienza (decreto-legge n. 59 del 2021, convertito, con modificazioni, dalla legge 1° luglio 2021, n. 101) (“PNC”).
In seno al Progetto, lo IEMEST opera in qualità di affiliato per gli Spoke 2 e 4 della “Fondazione D3 4 Health”, soggetto attuatore e referente unico (“HUB”) nei confronti del Ministero dell’Università e della Ricerca, appositamente costituita per l’attuazione, il coordinamento e la gestione dell’“Iniziativa” finanziata con il Fondo Complementare previsto dal Decreto Direttoriale n. 931 del 6 giugno 2022 “avviso per la concessione di finanziamenti destinati ad iniziative di ricerca per tecnologie e percorsi innovativi in ambito sanitario e assistenziale”.
La Fondazione – costituita da 28 partner tra Università pubbliche e private, Istituti di ricerca e Imprese – svolge attività di potenziamento della ricerca sulle tecnologie digitali in ambito sanitario, attraverso un sofisticato processo di data mining, al fine di migliorare diagnosi, monitoraggio e cure.
Abstract
Public health systems worldwide rely on limited resources and suffer the high costs of cure. This is especially true for Italy, where the universalistic system represents a precious asset for citizenship. The adoption of value-based healthcare (VBH) may mitigate these critical issues. In this scenario, the Digital Driven Diagnostics, prognostics, and therapeutics for sustainable Health care (D3 4 HEALTH) initiative aims at developing digital and biological twins to improve, through a data mining approach, reference diseases care.
D3 4 HEALTH initiative will deliver, adopting VBH, novel, non/minimally invasive predictive, diagnostic and therapeutic pathways for reference diseases: metastatic colon cancer, liver and bile duct cancer, central nervous system cancer, diabetes type I and multiple sclerosis. The project will be structured in four interlinked core Spokes, highly interrelated either at technical or translational level.
The deployment of the D3 4 HEALTH technologies will represent a tool for the achievement of National and European policy objectives combining the skills of referral with non-referral centres in Italy, for the development of cutting-edge service delivery systems. Specific objectives span from high-performance computing, such as AI solutions on a comprehensive interoperability data platform, development of innovative technologies and methods (wearable devices, biosensors and biomarkers) to obtain a cluster of digital information prototypical of the Digital and Biological Twin. The collection of digital data will be accomplished retrospectively at the beginning for a fast data accessibility from all referral centres. Then, the advanced devices and biomarkers will be further implemented in simulation tests and prospective longitudinal studies. Simulation strategies on Digital Twins, exploiting clusters of patient’s digital data, based on the query of AI and mathematical models, may generate predictive, prognostic and therapeutic response solutions. The simulated predictive algorithms may be validated by in-vitro developing biological simulation platforms, the Biological Twins, and by monitoring of the patient’s health condition, through advanced wearable technologies.
Sustainability of this approach will rely on the creation of research infrastructures (RI) equipped with stateof-art instrumentation for design, realization, and characterization of in-vitro biological twin of diseases and the development and testing of wearable sensors, biosensors and biomarkers for the digital twin. The RIs will be constituted by a headquarter and a few local nodes, open for research and technology services to the internal community of the D3 4 HEALTH initiative and to all interested stakeholders of the developed technologies.
From D3 4 HEALTH we envision successful technological solutions, the Digital and Biological twins, supported by a research infrastructure for reference diseases care.
The scientific and technical feasibility of the project relies on the high-level skills and international experiences of project partners and their ability to participate in multidisciplinary research involving enterprises. The duration of the project and the strong interaction with industries will ensure a successful implementation and sustainability of the project in the long-term. Communication, dissemination, and education will be promoted for public engagement and stakeholder involvement.
The deployment of the proposed solutions will have direct and indirect effect on the three axes around which the NRRP was built: promote digitalization and innovation, improve the Italian ecologic transition and advance social inclusion, especially concerning the North-South gap and ensuring equality in accessibility to the best care to all citizens.
An increase in public and private investment in R&D is expected given an effective collaboration between the public scientific base and the industrial world and the development of researchers’ skills, particularly in digital technologies, environmental transition and management models provided in D3 4 HEALTH.
The digital and biological twins proposed in the D3 4 HEALTH initiative will lead to better patient management and care, both in the shortand long-term. D3 4 HEALTH will achieve the goals of the national health system through the development of a research and clinical care digitized infrastructure, merging highly specialized technological centers and human expertise, based on an innovative model of integration of health data, for the development of state-of-the-art service delivery systems.
Finally, D3 4 HEALTH will strengthen the position of Italy in the landscape of European technological advancement for the diagnostic and therapeutic reference diseases pathways and will impact the centrality of the person, the protection of the right to health, the collaboration between different levels of government, the optimization of resources and the return of health to the population.
Promuove lo sviluppo di modelli predittivi, diagnostici e terapeutici innovativi, avvalendosi delle tecnologie digitali più avanzate, rappresentate da algoritmi di Intelligenza Artificiale, dispositivi e sensori indossabili, nonché Network Analysis. Espressione di avanzamento della ricerca scientifica con inevitabile risonanza sull’impatto clinico e di conseguenza, sull’ottimizzazione della cura del paziente sarà rappresentato dallo sviluppo di un Digital Twin e di un Biological Twin.
Rappresenta una grande opportunità per i giovani ricercatori, offrendo la possibilità di far parte di un programma di R&S finalizzato all’innovazione del sistema sanitario attraverso la transizione tecnologica digitale, in cui Ricerca e Impresa si incontrano per promuovere e sostenere congiuntamente ricerca di alto livello, trasferimento tecnologico e alta formazione.
Determina – attraverso le tecnologie digitali innovative sviluppate in collaborazione tra i Partner – un impatto temporale specifico sulla salute dei cittadini nel:
Leader: Università degli Studi di Salerno
Co-leader: Università Vita-Salute San Raffaele, Fondazione Bruno Kessler
Affiliates: AizoOn, CINECA – Consorzio Interuniversitario per il Calcolo Automatico dell’Italia del Nord Orientale, IRCCS Galeazzi – Sant’Ambrogio, Istituto Euro-Mediterraneo di Scienza e Tecnologia, Istituto Europeo di Oncologia, Politecnico di Bari, Porini SRL, Telethon Institute of Genetics and Medicine (TIGEM)
Spoke 2 integrates different multidisciplinary professional expertise with the aim of supporting the generation of innovative AI solutions for data collection and analysis in healthcare. The mission is to achieve a shared and distributed platform collecting clinical data from patients, both in the raw form and pre-processed, that can open new frontiers in medical research. The analysis of such data and the generation of clusters of patients who share similar physical parameters and clinical conditions may represent a step forward in understanding the clinical response of patients to certain treatments, thus contributing to creating new knowledge for the diagnosis and prevention of tumor diseases as well as for the assessment of the risk and expected response to a therapeutic plan. In this perspective, the generation of Digital Twins that are representative of a specific population of patients, can provide a digital research tool to perform preventive analysis of the treatments and suggest new parameters for further separating the cohorts of patients.
Sito della fondazione: https://sites.google.com/uniroma1.it/d3forhealth/home