MEDVIEW builds on the growing recognition that achieving good health in a community requires much more than medical and technical solutions available only in selected places and circumstances. Citizens’ health priorities stem from their everyday experiences and needs and differ from professionals’ priorities. There is a growing demand for a more "human-centric" approach to tackle the complexity of achieving overall human well-being. It is widely accepted that involving citizens in the design of products, services, and policies that impact their health, lives, and communities is thought to improve their overall quality and effectiveness. Citizens’ voices can act as a mechanism for change ensuring that the created solutions are more integrated around communities’ needs instead of centered on organisations’ traditional remits. MEDVIEW aims to create an enabling environment for innovation, collaboration, and effective co-creation between industry partners, citizens (patients, community members), health practitioners, doctors, researchers, academia, and policymakers to address the complex issue of human health & well-being. To succeed so, we have carefully selected partners from three WIDENING countries [LT, GR, SLO] and two of non WIDENING countries [LUX, BE] addressing the following selection criteria: - Wide geographical reach, representing a rich tapestry of cultures, languages, and healthcare/wellbeing systems - Specialized expertise and a solid track record of all partners in coordination and support activities both at the national as well as in an international level - Representation of all target groups as defined by the Call The project will ultimately deliver the MEDVIEW Knowledge Valorisation Implementation Guide, a complete practical guide, and the relevant tools comprised of methods, practices, and procedures for the deployment of an open innovation space for effective knowledge valorisation in the field of well-being.

VOCORDER develops innovative components based on disruptive technologies that aims to render breath analysis testing a holistic, highly efficient health monitoring apparatus that can be seamlessly integrated into everyday life. The project capitalizes on recent developments on mid-infrared lasers and moves the technology well beyond the state-of-the-art to demonstrate at TRL5 a highly efficient multiple species (gases) breath analysers that can with a 5 sec use of the device, and the use of artificial intelligence-based signal processing, can conclude on the health status of the individual, just like the fictional Star Trek Tricorder. To record and analyze the maximum amount of information on the individual health status completely unobtrusively, exhaled breath is among the most convenient body fluids as can be obtained at large quantities, practically without any causing discomfort to the user, with strong potentially to seamlessly integrate into everyday life. Exhaled breath contains more than 1000 substances which can serve as efficient biomarkers, the measurement of concentration of which can provide a clear provision of the health status of the individual while the diagnosis of some diseases or pathological process in human body can be obtained early. For a truly seamlessly integration in a plethora of settings, VOCORDER examines the ways to render the final instrument compact and potentially inexpensive.

ArtifArtificial Intelligence (AI) will revolutionize healthcare as its diagnostic performance approaches that of clinical experts. In particular, in cancer screening, AI helps patients to make better-informed decisions and reduce medical error. However, this requires large datasets whose collection faces severe practical, ethical and legal obstacles. These obstacles can be overcome with swarm learning (SL) where partners jointly train AI models without sharing any data. Yet, access to SL technology is seriously limited because no studies have implemented SL in a true multinational setup, no practically usable implementation of SL is available, researchers & healthcare providers have no experience with setting up SL networks and policymakers are currently unaware of the broader implications of SL. ODELIA will address & solve these issues: ODELIA will build the first open-source software framework for SL, providing an assembly line for the streamlined development of AI solutions. To serve as a blueprint for future SL-based AI systems, ODELIA partners collaborate as a swarm to develop the first clinically useful AI algorithm for the detection of breast cancer in magnetic resonance imaging (MRI). The size of ODELIA's distributed database will exceed all previous studies and ODELIA's AI models will reach expert-level performance for breast cancer screening. Thereby, ODELIA will not only deliver a useful medical application, but prove the clinical benefit of SL in terms of accelerated development, increased performance and robust generalizability to ultimately save thousands of lives of European patients. ODELIA's success will push partners to serve as nuclei for the exponential growth of the SL network and extend SL to a multitude of medical applications. Thus, patients, healthcare providers and citizens in Europe will be provided with a digital infrastructure that enables development of expert-level AI tools on big data without compromising data safety and data privacy.

Pharmaceuticals have undoubtably made our world a better place, ensuring longer and healthier lives. However, pharmaceuticals and their active metabolites are rapidly emerging environmental toxicants. It is thus critical that we fully understand, and mitigate where nec-essary, the environmental impact resulting from their production, use and disposal. In this direction, ENVIROMED addresses two aspects of the environmental impact of pharmaceuticals, a) impact of the processes in manufacturing the compound, and b) impact of the compound itself, during its lifecycle. The project narrows the knowledge gap when it comes to the effect of pharmaceutical compounds, and their derivatives, in the environment as it enables the better understanding the environmental impact of such compounds, throughout their lifecycle. It aims to offer (via extensive monitoring campaigns & scientific studies) information regarding occurrence of pharmaceuticals in the environment, their persistence, environmental fate, and toxicity (via in-vitro & in-vivo models) as well as application of in-silico methods to provide information about the basic risk management and fate prediction in the environment. Brief ideas about toxicity endpoints, available ecotoxicity databases, and expert systems employed for rapid toxicity predictions of ecotoxicity of pharmaceuticals will also be taken into account, in order to have a comprehensive approach to pharmaceuticals' Lifecycle Assessment (LCA). Moreover, the project aims at developing a set of technologies that enable greener and overall, more efficient pharmaceuticals production, which include: a) Green-by-design in-silico drug development; b) Novel sensing to allow reduction of rinsing chemicals and cycles; c) a robust Continuous Biomanufacturing line (CBM), which makes use of AI-enabled process optimisation and prediction, using data assimilation based on chemical sensing and energy disaggregation/monitoring. Training activities and a robust exploitation