The SHIELD project seeks to revolutionise early detection of pancreatic cancer, focusing on individuals with high heritable genetic risk. Pancreatic ductal adenocarcinoma (PDAC) has a 5-year survival rate of less than 10%, primarily due to late-stage diagnosis. Consequently, 85% of PDAC cases are identified too late for curative treatment. However, early detection can significantly improve outcomes, increasing the survival rate to 42% with surgical intervention. SHIELD aims to validate a new blood-based diagnostic test designed for early PDAC detection in high-risk individuals and pilot an early detection programme in seven EU countries, targeting individuals with familial or genetic predispositions. It will also identify new protein biomarkers for other high-risk indications, such as new-onset diabetes (NOD). Collaboration with national screening authorities will help integrate this test into existing programs, and partnerships with patient organizations will enhance recruitment. SHIELD envisions transforming pancreatic cancer diagnostics by increasing the 5-year survival rate to 30% by 2035 in Europe.

Press Release 1 – May 2025

Funded by the European Union (European Commission, HORIZON-IA – HORIZON Innovation Actions)

The European population growth is slowing down, while the population ageing accelerates. Within Europe’s ageing population, Hearing Loss, Cardio Vascular Diseases, Cognitive Impairments, Mental Health issues and Balance Disorders, as well as Frailty, are prevalent conditions, with tremendous social and financial impact.

Preventing, slowing the development of or dealing effectively with the effects of the above impairments can have a significant impact on the quality of life and lead to significant savings in the cost of healthcare services. 

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 857172.

Interdisciplinary approach and individualized treatment plan are key points for successful management, due to the great heterogeneity of symptoms. 

All around Europe, ENT physicians, audiologists, psychiatrists, psychologists, neurologists, behavioral neuroscientists, general practitioners, nurses, customer advocates, psychoacousticians, basic scientists and patient representatives work on providing highly personalized upto-date diagnostic and management services and collaborate in varied research projects focusing on tinnitus pathophysiology, assessment and possible cures.

The overall aim of the Erasmus+ project Tin-TRAC is to utilize co-creative principles to develop digital learning resources that will Integrate tinnitus assessment and management in terms of clinical and research practice throughout EU.

As such, the main goal is the development of an EU-wide e-Learning platform, that will support a multidisciplinary applicable, standardized curriculum on Tinnitus assessment procedures and treatment recommendation, integrating research and clinical practice. 

Objectives

• Provide a pan-European framework for interdisciplinary exchange of knowledge and cooperation
• Identify the best practices, policies and methods regarding specialized training across Europe and organize customized training programs for researchers and clinicians throughout different European facilities.
• Offer the possibility of collaboration with organisations in other sectors in order to stimulate a more comprehensive, rapid, effective and long-term response to tinnitus patients
• Exploit co-creative practices on the preparation and dissemination of comprehensive high quality educational material on globally accepted guidelines on tinnitus assessment and management 
• Train possible future trainers of health care professionals. Multiply impact, create long-term effect

Who will benefit

Project’s outcome will be available to a wide audience of healthcare professionals, clinicians and researchers.

Tin-TRAC is a Joint Project funded by the European Commission within the ERASMUS+ 2021 Programme, Key Action 2 – KA220-VET – Cooperation partnerships in vocational education and training

is a H2020 funded project conceived to support clinical decision making, clinical monitoring and data-driven interventions for heart failure patients in need of ventricular assist devices (VAD) and patients who received a heart transplant.

Heart failure patients management has a huge impact on health systems due to the required multiple and prolonged hospitalisations of patients and the related patient management costs. Focusing on routine patient-physician or patient-nurse communication following discharge can result in a significant reduction of hospitalizations.

THE HEART OF RETENTION RESEARCH 

RETENTION project is exploiting the technological convergence of state-of-the-art technologies, to develop innovative, transparent, and sophisticated decision-making capabilities and deliver personalized effective interventions for advance heart failure diseases.

GLOBAL INSIGHT CLOUD

The platform supports clinical decision making and evidenced based personalised interventions for HF patients by:

Data analytics using innovative model-driven big data methods, statistical approaches, artificial intelligence and machine learning techniques.

Applying transparent, explainable and verifiable decision making capabilities that leverage the evidence produced by the underlying data analysis and augment clinical studies targeting HF and, potentially, other CVDs.

CLINICAL SITE BACKEND

Patterns detection in the HF disease progression and the quality of life of patients.

Cross checking and validation against the clinical literature.

PATIENT EDGE

Continuous monitoring of medical, clinical, physiological, behavioural, psychosocial, and real-world data for the patients.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 965343.

Specifically the main research objectives of the project are:

(i) Explore and identify system-specific cyber-physical weaknesses posing security, privacy, and safety threats, in autonomous mobile robots operating in a healthcare environment;

(ii) Analyse surfaced vulnerability issues in conjunction with projected threats and propose defence measures and mitigation strategies towards safeguarding mobile robots operation.

(iii) Define and standardize a minimal set of vulnerability testing procedures and guidelines leveraging and extending the Robot Vulnerability Scoring System for safe and autonomous robotic fleet management in a “safety-critical setting”. The project will be implemented through staff exchanges among different organizations with complementary expertise in cybersecurity, healthcare, cloud computing and robotics from 5 countries across EU promoting transfer of knowledge between industry and academia.

This project has received funding from the European Union’s MSCA programme under Grant Agreement n°101007673.

The goal of Rehabotics is multiple:

Objective 1: Faster recovery of functional extremities due to neurological disorder or neurodegenerative disease and reduction of pain due to spasticity.

Objective 2: Creating an innovative medical decision support system that promotes personalized rehabilitation through retraining of motor disorders, therapeutic strengthening exercises, assistive technologies.

Objective 3: Enhance patient-clinician interaction that helps to improve therapeutic outcomes and allows for the automatic adjustment of treatment planning according to patient performance.

Objective 4: Improving the quality of life of patients and their families by implementing a system that allows exercise from home and remote monitoring and significantly reduces the frequency and cost of the need to visit a specialized physiotherapy center.

Objective 5: The improvement of the level of robotics capabilities in the Greek industry as well as in the provision of services aiming at the following characteristics: adaptability, cognitive ability, structurality, autonomy in decision making, flexibility, interaction ability, handling ability, movement ability, perception ability.

Objective 6: The compilation of a feasibility study and a rights study.

• Identify a subset of protein biomarkers for early CRC screening and understand their regulatory role through protein network analysis.
• Conduct pilot studies at clinical sites to validate the proposed protocol and refine findings using standardized prospective data.
  Utilize state-of-the-art AI tools to detect significant biomarkers and risk factors related to CRC incidence in an objective and measurable manner.
• Assess the effects of an extended risk factor set on CRC, offering behavioral interventions through a user-friendly mobile tool to impact modifiable pre-malignant states.
• Advocate for change in CRC screening guidelines by providing policy makers with evidence-based data to inform decision-making on potential policy reform.
• Investigate DIOPTRA’s expandability and network with ongoing / future cancer initiatives to empower the newly launched Knowledge Centre on Cancer, enhancing usability and accessibility for early user-friendly screening.

DIOPTRA is organized into 5 distinct phases:

• Phase 1: Retrospective data collection, tissue / liquid biopsy samples, demographic and other relevant data, organize knowledge into standardized format, generate DIOPTRA homogenized dataset.
• Phase 2: Risk factor investigation, initial stage of liquid biopsy biomarker analysis (early discovery), produce holistic CRC risk factor set and set of biomarker ‘hits’.
• Phase 3: First stage of prospective data collection, acquire risk factors information and liquid / tissue biopsy pairs, analyze extended pool of samples for biomarker development, generate protein features for training and evaluating DIOPTRA AI model.
• Phase 4: AI-based analysis for generating discriminative protein biomarkers, develop full stratification model using hybrid approach, incorporate knowledge into DIOPTRA mobile app for personalized behavioral interventions.
• Phase 5: Clinical validation and real-settings feedback, define implementation needs for healthcare upscaling, incorporate full DIOPTRA solution into prospective studies.

https://www.dioptra-project.eu