The aim is to coordinate technological development, promote participatory approaches, and increase awareness.
The objective is to harmonize procedures for evidence collection in the pilots of Spoke 2 and Spoke 3. Processes, outcome indicators, and impact indicators will be mapped and listed to enable a multidimensional evaluation of preventive digital approaches.
The needs and requirements from the pilots of Spoke 2 and Spoke 3 will be collected in order to coordinate the development of solutions in WP2, WP3, and WP4.
Stakeholders such as researchers, funding agencies, health authorities, healthcare professionals, patients, citizens, and innovators will be identified. A dedicated platform will ensure their active engagement.
Synergies with relevant initiatives will be established through a mapping exercise and ongoing networking.
Communication and dissemination activities of the results, organization of workshops and public events.
Overcome barriers related to compliance with legal, ethical, and data protection requirements.
Mapping of the ethical framework applicable to the specific context and identification of any critical situations.
Analysis of privacy regulations, with particular attention to the GDPR.
Identification of regulatory requirements and relevant legal issues for the pilots.
Analysis of the civil liability regime applicable to the examined cases in light of European and international regulations.
Enable different information systems, devices, and applications to access, exchange, integrate, and use data among the stakeholders involved in the pilots of Spoke 2 and Spoke 3.
This task will establish a direct link with the parties involved in the pilots to ensure the implementation of solutions at the pilot sites. Interoperability governance will be applied to solutions provided by external vendors and to existing systems involved in the pilots (legacy systems).
Best practices for data management will be adopted in line with the FAIR principles, supporting end users in making data and services available and accessible.
Tools and methods for adopting national and European standards (e.g., HL7 CDA for EHR, DICOM for diagnostic images, SNOMED, LOINC, HL7 FHIR).
The aim is to identify, develop, adapt, and customize enabling technologies.
Identification, adaptation, and development of computing solutions in line with the requirements of the pilots of Spoke 2 and Spoke 3. This includes both cloud and on-premise solutions.
Definition of effective approaches for integrating machine learning (ML) models into ML-based software systems.
Identification and development of tools based on the data used in the pilots, including techniques to explain ML models.
Development of embedded/wearable devices and mobile apps for detection, feedback, and front-end solutions in the pilots.
Starting from the synthesis of the evidence in Spoke 2 and Spoke 3, the goal is to understand and anticipate the impact of the new solutions and promote their scalability.
This task will evaluate the impact of the proposed innovations in addressing gaps and inefficiencies by leveraging enabling digital technologies. Improved organizational models will be identified through a rigorous research design to generate high-quality evidence. Specific indicators will be collected in Spoke 2 and 3 to verify effectiveness and efficiency in real-world settings.
The results of Task 5.1 will be used to accelerate adoption and strengthen innovation potential, in coordination with Task 1.3 of WP1.
This task will enable partners and stakeholders to identify any legislative gaps and constraints in current organizational models, with a focus on personalized digital prevention aimed at well-being, not just disease control. Recommendations will be produced to address regulatory, legal, and policy issues.
Addressing the shortage of qualified personnel and improving the level of digital skills in the context of healthcare prevention required by employers and employees.
Enhancement of postgraduate university courses and doctoral programs with a focus on advanced digital skills in the healthcare sector, particularly in prevention and health promotion.
Development and provision of advanced postgraduate courses to prepare professionals for emerging roles in the digital era (e.g., Data Steward, Data Custodian).
Creation of career opportunities in academic and industrial fields for fixed-term staff hired within this initiative.
Ensure the long-term sustainability of Spoke 1 and the protection and enhancement of results. Innovative systems and methodologies for intellectual property management will be developed, in coordination with the corresponding WPs of Spokes 2 and 3
Design and implementation of initiatives to ensure the sustainability of Spoke 1, including the stabilization of relationships and the adoption of intellectual property management strategies to secure funding.
Ongoing inventory of intellectual property, co-ownership strategies, protection, and exploitation strategies.
AI/ML techniques will be used to support maturity and scalability strategies.
Assessment of opportunities for the creation of new enterprises based on research results, including incubation activities.
Collection and addressing of the needs of all WPs in Spoke 1 for the acquisition of external goods and services functional to WP activities.
Develop a multidisciplinary, inter-institutional framework supported by advanced digital infrastructure for innovative community-based surveillance and digital primary prevention.
A network of institutions and stakeholders will be established through dedicated agreements, including data sharing. A multidisciplinary team will coordinate the pilots and activities within Spoke 2 and with the other Spokes, contributing to the activities of WP1 of Spoke 1.
Coordination for the implementation of an advanced IT infrastructure for high-performance computing in compliance with the standards and interoperability profiles developed in Spoke 1. The infrastructure will integrate health, occupational, environmental, and climate data.
Development and provision of services for data access and processing: database services, API interfaces for web and mobile connection, and AI/ML-based services for centralized and federated models.
Sharing of opinions and needs regarding data management, service organization, business models, and funding opportunities.
Develop and enhance advanced digital functions for innovative community-based surveillance, primary prevention, and emergency response.
The digital infrastructure deployed in WP1 will support an innovative cancer surveillance system based on data-driven models and state-of-the-art ML techniques with advanced functions for:
a) integration of epidemiological data with environmental, occupational, and lifestyle data to improve primary cancer prevention;
b) interoperability between clinical registries, biobanks, and high-resolution studies;
c) developing advanced models to assess the effectiveness of preventive interventions.
Creation of a web platform to collect and cross-reference health, environmental, and individual data in order to:
a) study the effects of environmental exposure on health in different target populations;
b) adopt an “Assess, Warn & Response” (AWARE) approach to protect public health and the environment from the impacts of severe pollution;
c) prepare for infectious diseases and antibiotic resistance.
Multidisciplinary approach to estimate individual and cumulative risks from emerging pollutants and to develop safer and more sustainable management strategies for technological products.
To develop and implement new digital approaches to prevent occupational and environmental risks and promote population health.
Collection of individual data on lifestyles, health determinants, and genomic data for systematic and longitudinal surveillance. Development of descriptive and predictive models for complex diseases.
Expansion of the digital infrastructure to conduct community intervention trials to evaluate the effectiveness of digital tools in primary prevention and personalized approaches.
Involvement of older workers vulnerable to technological transformations to study the role of environmental sensors and wearables. A similar approach will be applied to young workers in their first job experiences.
Evaluation of the effectiveness of programs to prevent gastric, liver, cervical, and oropharyngeal cancers. Extension of these programs to the family members of recruited healthcare workers.
To design, implement, and demonstrate how digital tools for primary prevention can support integration and effectiveness between primary and hospital care.
Combination of monitoring and prediction models using data analysis and big data techniques to detect changes in daily hospitalization trends at different spatial and temporal scales.
Development of innovative pathways to improve collaboration between community and hospitals in vaccination programs, with digital tools such as computerized bookings and artificial intelligence to analyze vaccine hesitancy.
Implementation of low-cost technologies to prevent falls and injuries on a large scale. ML-based analyses to develop robust risk models.
Experimentation with innovative primary interventions based on motivational approaches and digital platforms.
Establish an epidemiological framework for the optimal utilization of biological, clinical, psychological, social, and environmental data collected in real-world settings, in order to enable personalized risk prediction for specific diseases and more effective preventive strategies throughout the entire lifespan.
Data will be collected from real-world sources and research studies, covering the period from prenatal stages to old age. Requirements and methods for interoperability profiles and standards will be identified, in coordination with WP3 in Spoke 1.
The data model will be expanded to include health-related data, such as socioeconomic and environmental information.
These will be conducted using advanced risk stratification analyses and innovative modeling approaches.
To include recruited communities and established cohort consortia.
The valorization of results will be assessed together with WP2 in Spoke 1.
Addressing the shortage of qualified personnel and improving the level of digital skills in epidemiological surveillance, health promotion, and primary prevention.
Ensure the long-term sustainability of Spoke 2 and the valorization/exploitation of research results, with positive impacts on communities and stakeholders.
Coordinate the implementation of pilots, collect evidence and process indicators, promote participatory approaches, and increase awareness. The tasks reflect and are coordinated with the activities of WP1 in Spoke 1.
Provide digital models of the human body. Mechanistic models, such as Digital Twins, will be applied as modern In-Silico Trials to replace in vitro, animal, and human experiments in the assessment of the safety and efficacy of new treatments.
Development and validation of fracture risk predictions using Bologna Biomechanical Computed Tomography (BBCT).
Combination of Digital Twin technology and muscle strength analysis to explore factors contributing to joint overload.
Computerized planning to slow the progression of osteoarthritis and delay the use of joint prostheses.
Retrospective analysis of image series (X-rays, CT, MRI).
Identification of radiomics-based features to predict post-surgical complications.
Correlations between traditional screening tools and neuropsychological assessments.
Development of personalized protocols for children with cerebral palsy and other at-risk group.
Testing the effectiveness of AI in predicting the risk of complications and the effectiveness of treatments in various non-communicable and communicable diseases, across different age groups.
Use of AI and ML to predict the risk of infections and acute cardiovascular events.
Analysis of cancer-associated subnetworks for early predictions and survival.
Application of predictive models to diabetic complications and NAFLD.
Identification of individuals at risk for preclinical conditions and progression toward intellectual disability.
Identify new biomarkers for the early diagnosis of pathological conditions using innovative and large-scale personalized technologies.
Improve patient care pathways across different pathophysiological conditions and ages by leveraging platforms that integrate data registries, wearable sensors, and IoT technologies.
Addressing the shortage of qualified personnel and improving the level of digital skills required in the context of healthcare prevention.
Ensure the long-term sustainability of Spoke 3 and the protection and enhancement of research results.