Integrated, high-quality personal health data (PHD) represents a potential wealth of knowledge for healthcare systems, but there is no reliable conduit for this data to become interoperable, AI-ready and reuse-ready at scale across institutions, at national and EU level. AIDAVA will fill this gap by prototyping and testing an AI-powered, virtual assistant maximizing automation of data curation & publishing of unstructured and structured, heterogeneous data. The assistant includes a backend with a library of AI-based data curation tools and a frontend based on human-AI interaction modules that will help users when automation is not possible, while adapting to users? preferences. The interdisciplinary team of the consortium will develop and test two versions of this virtual assistant with hospitals and emerging personal data intermediaries, around breast cancer patient registries and longitudinal health records for cardio-vascular patients, in three languages. The team will work around four technology pillars: 1) automation of quality enhancement and FAIRification of collected health data, in compliance with EU data privacy; 2) knowledge graphs with ontology-based standards as universal representation, to increase interoperability and portability; 3) deep learning for information extraction from narrative content; and 4) AI-generated explanations during the process to increase users? confidence. By increasing automation of data quality enhancement, AIDAVA will decrease the workload of clinical data stewards; by providing high-quality data, AIDAVA will improve the effectiveness of clinical care and support clinical research. In the long-term, AIDAVA has the potential to democratise participation in data curation & publishing by citizens/patients leading to overall savings in health care costs (through disease prevention, early diagnosis, personalized medicine) and supporting delivery of the European Health Data Space.

Pancreatic cancer has the lowest survival rate amongst other cancers and is responsible for 95,000 deaths every year in the EU. Its treatment is usually palliative, aiming at slowing tumour progression and at symptom management. The main hypothesis of RELEVIUM is that quality of life (QoL) of advanced pancreatic cancer patients can be significantly improved by reducing pain and cachexia through highly personalised nutrition, physical activity, and pain management strategies, in addition to chemotherapy treatment. To achieve this, RELEVIUM will empower patients with digital tools that facilitate patient-doctor communication and enable them to self-manage their disease. RELEVIUM will use (i) a multi-sensor smartwatch and an innovative remote ultrasound patch, (ii) AI algorithms for continuous remote monitoring of pain and sarcopenia, as well as for decision support, and (iii) patient and caregiver applications. Combined, these tools will provide a stream of evidence on symptom progression and will enable physicians to apply personalised care plans. RELEVIUM brings together an interdisciplinary team of experts and will also involve patients and their caregivers in an iterative co-creation process. The project will initially conduct a feasibility and data collection study (RELEVIUM-FDC, n=130). The study aims at optimizing patient adherence and compliance, and at collecting data for the development of the intervention. A five-centre randomized clinical trial (RELEVIUM-RCT) will then evaluate the efficacy of the proposed personalised care plans for advanced pancreatic cancer patients (n=132) in terms of their QoL. Several secondary outcomes will be investigated, such as the cost-effectiveness of the intervention, its potential in increasing health equity and in relieving the stress burden on the patient families. The study outcomes will result in recommendations for integrating remote monitoring and improving QoL outcomes in palliative care for advanced pancreatic cancer

SF4S is a collaborative action with partners from HEIs, VET providers, innovation networks and business entities from the Agri-food, Health and the Mobility sectors. It supports our transition to a more sustainable European economy by helping to address the lack of green, digital and future (i.e. sustainability foresight) skills among students and professionals and by connecting knowledge flows between HEI, VET and industry actors that are necessary for Europe to develop cooperative solutions on a large-scale and support the recommendations for action in the major reports: Green Deal, NextGenerationEU, European Skills Agenda and OECD Future of Education and Skills 2030. We do this by advancing and scaling an innovative approach that we call Strategic Foresight for Sustainability (SF4S) based on best practices and methods from corporate foresight, sustainability management, green business models, digital skills and green product/service development across value chains and industries. SF4S is based on an entrepreneurial cooperative approach in our community of practice of 250 industry professionals and 100 HEIs, which develop engagement and insight from the three industries through 130 interviews, four large-scale co-development projects and the development, testing and deployment of learning and training materials for HEIs, VETs and business sector through the community. The ambition is pan-European, and 400 students will initially be reached through the SF4S project and its open access materials. The living community of practice will scale beyond the project itself, and into other industries. The long-term impact, which in itself is a starting point for European-wide transition, will be three industries adopting new sets of futures and future sustainability foresight skills, and both VET and HEI students entering the workforce with Foresight for Sustainability skills that enable them to create actions that support the long-term green transition that Europe needs.

Hospital wastewater (HWW) poses a significant environmental and health risk due to the presence of pharmaceuticals, pathogens, and other hazardous substances that are administered in healthcare institutions. Unfortunately, current urban wastewater treatment (WWT) plants are not capable of effectively removing many of the pollutants generated by hospitals. As a result, these contaminants reach and accumulate in natural water bodies, threatening ecosystems and biodiversity, and public health through the contamination of drinking water or food. In addition, public health is also menaced by HWW as it contains important amounts of antibiotic-resistant microorganisms and genes. In fact, Antimicrobial Resistance (AMR) is one of the greatest health threats of our times. While most common medicines are consumed in households, specialized drugs such as cytostatic drugs, some antibiotics, or X-ray contrast agents are mainly distributed in hospitals. Furthermore, HWW is a hotspot for the transmission of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARG). To reduce the risk associated to these contaminants, it is key to remove them as close to their source as possible, and before they are discharged to the municipal water network. Despite the existence of different technologies that efficiently remove contaminants from HWW, currently, there is no single process that can be used for the comprehensive treatment of HWW regarding the elimination of a mix of pollutants to a high degree. Moreover, technology may be further developed to be more efficient, environmentally sustainable, and cost-effective for hospitals. In this context, the main objective of THERESA PCP is to launch a pre-commercial procurement process (PCP) based on the development of an environmentally sustainable on-site system to decontaminate HWW, being capable of effectively removing, among other contaminants, cytostatic drugs, X-ray contrast agents, antibiotics, ARB and ARG, from HWW.

The objective is to create a network/community/ecosystem of procurers and relevant stakeholders in PPI. The idea is to empower all the actors involved in PPI through this network, focusing on the procurers. We need to attract both experienced procurers and not experienced procurers if we want to succeed in this. We will also need to analyse current barriers and needs of procurers, and then create and shared tools to facilitate PPI for all the actors involved.