PHOENi²X aims to design, develop, and deliver a Cyber Resilience Framework providing Artificial Intelligence (AI) - assisted orchestration, automation & response capabilities for business continuity and recovery, incident response, and information exchange, tailored to the needs of Operators of Essential Services (OES) and of the EU Member State (MS) National Authorities entrusted with cybersecurity. Through the deployment PHOENi²X Cyber Resilience Centres (PHOENi²X CRCs), OES will gain: (i) enhanced Situational Awareness with AI-assisted Prediction, Prevention, Detection & Response capabilities, and business risk impact assessment-based prioritisation; (ii) proactive and reactive Resilience Automation, Orchestration, and Response (ROAR) mechanisms, providing Business Continuity, Recover and Cyber & Physical Incident Response; (iii) Increased Preparedness through relevant Serious Games and realistic Resilience Cyber Range (RCR) Assessment & Training; (iv) timely and actionable Information Exchange between OES, National Authorities and EU actors, leveraging interoperable and standardised alerting and reporting mechanisms and processes.

Heart failure (HF) is a prominent chronic disease, despite efforts in improving its prevention, diagnosis and treatment, represents the leading cause of disability and premature death throughout the world, while being is a heavy burden on health systems due to the multiple, prolonged hospitalizations required for patients suffering from it and the related management costs. Nevertheless, studies have shown that routine patient-physician or patient-nurse communication following discharge can result in significant reduction of hospitalizations. The pertinent collected patient data may include simple yet important information (e.g. patient weight), as well as previously difficult to obtain information such as routine ECG, ICD/CRT-D interrogation and pulmonary arterial pressure monitoring, which are now within reach due to technological progress. Motivated by the above, RETENTION aims to develop and deliver an innovative platform supporting enhanced clinical monitoring and interventions aimed at improving the clinical management of patients with chronic HF, reducing their mortality and hospitalisation rates, and improving their quality of life, safety, and well-being. The RETENTION platform will support clinical decision making and evidenced based personalised interventions for HF patients by: (a) continually monitoring and collecting medical, clinical, physiological, behavioural, psychosocial, and real-world data for such patients, (b) analysing these data using innovative model-driven big data analytics, statistical, artificial intelligence and machine learning techniques, (c) detecting patterns in the HF disease progression and the quality of life of patients, (d) cross checking and validating them against the clinical literature, and (e) offering transparent, explainable and verifiable decision making capabilities that leverage the evidence produced by the underlying data analysis and augment clinical studies targeting HF and other CVDs.

Current evidence from both randomized trials and real-world evidence studies suggests that older breast cancer patients derive clinical benefit from the addition of CDK 4/6-inhibitors to endocrine therapy but with higher risk for adverse events and treatment discontinuation compared to younger patients. The IMPORTANT project will design and conduct a pragmatic clinical study with a decentralised approach for older patients with advanced breast cancer aiming at high level of evidence (level I) with multi-layer results that can enable changes in current clinical practice. This study will be conducted across 6 (six) EU countries, and will include more than 500 female and male patients. The project will also perform a series of analyses over a) a wide range of clinical-relevant primary and secondary endpoints targeting to contribute to current clinical practice and b) the implementation of specific strategies aiming at more individualized treatment and follow-up approaches to a clinical trial setting that highly resembles real-world setting due to the trial's pragmatic design. The project will be developed in 60 months by a competitive consortium of 19 partners from 11 countries, which corresponds to a well-balanced structure, involving clinical sites, SMEs, universities and patient advocacy organizations. Despite the great diversity of entities within the proposal, IMPORTANT partners bring state-of-the-art complementary skills ensuring the ability of the consortium to successfully complete the proposed work.This action is part of the Cancer Mission cluster of projects on ‘Diagnosis and treatment’.

FELICE aspires to design the next generation assembly processes required to address urgent needs in manufacturing. It unites multidisciplinary research in robotics, AI, computer vision, data analytics, process optimization and ergonomics to deliver a modular platform capable to integrate and harmonize an array of autonomous and cognitive technologies aiming to increase the agility and productivity of an assembly production system and also ensure the safety and physical and mental well-being of human workers. To achieve these goals, technologies will be developed combining the accuracy and endurance of robots with the cognitive ability and flexibility of humans. Such flexible and configurable technologies will support future manufacturing assembly floors to become agile, and address Industry4.0 adaptation. We consider two layers of operation, control and processing, a local one introducing i) a collaborative assembly robot roaming the shop floor to assist workers in assembly tasks, and ii) adaptive workstations for optimizing worker-specific ergonomic aspects, and a global layer which will sense and operate upon the real world via an actionable digital replica of the physical assembly line. FELICE will i) implement perception and cognition capabilities allowing the system to build context-awareness, ii) advance human-robot collaboration in otherwise manual assembly lines, enabling robots to safely and ergonomically share tasks with humans, allowing the flexible reconfiguration of an assembly production process and, iii) realize a manufacturing digital twin, i.e. a virtual representation tightly coupled with production assets and the actual assembly process to enable the management of operating conditions, the simulation of the assembly process and the optimization of performance aspects and, iv) integrate developments in an industrial assembly line for agile production. FELICE has two pilot environments: one for technology validation and one related to car assembly.

SYNAPSE aims to design, develop & deliver an Integrated Cyber Security Risk & Resilience Management Platform, with holistic Situational Awareness, Incident Response & Preparedness capabilities. The proposed platform will encompass: (i) Incident Response through process automation and orchestration mechanisms, also covering organisational/business aspects (e.g., business continuity processes); (ii) AI-enhanced Situational Awareness, encompassing extraction & analytics of actionable and pertinent Cyber Threat Intelligence (CTI), along with attack early warning & threat hunting systems; (iii) Preparedness through cybersecurity, privacy & business continuity training, covering different training delivery means, allowing it to tailor the delivery method to the content; (iv) Technical & economic risk management, integrating outputs of (i)-(iii) above and supporting risk-benefit analyses (including what-if scenarios) to inform decision-making and enable risk transfer schemes with Smart Contract-enabled cybersecurity insurance; (v) Continuous feedback between (i)-(iv) above, along with standards-based sharing, alerting & reporting (intra- & inter- Member State), based on outputs of (i)-(iii) above, thus enabling the establishment of shared situational awareness, coordinated response and joint preparedness