Non-Alcoholic Fatty Liver Disease (NAFLD), including its more pathologic consequence, non-alcoholic steatohepatitis (NASH), is believed to be the most common chronic liver disease worldwide, affecting between 6 to 37% of the population. NAFLD is a so called ‘silent killer’, as clinical symptoms only surface at late stages of the disease, when it is no longer treatable: untreated, NAFLD/NASH can lead to cirrhosis and hepatocellular carcinoma, culminating in liver failure. Currently the best method of diagnosing and staging the disease is liver biopsy, a costly, invasive and somewhat risky procedure, not to mention unfit for routine assessment. Besides, no therapeutic consensus exists for NAFLD/NASH treatment. mtFOIE GRAS (Foie Gras being French for "fat liver") proposes to address the pressing need for non-invasive, accurate, rapid assessment of NAFLD/NASH stages, before and after intervention, through the development of biomarkers and innovative tools to follow mitochondrial (mt) dysfunction, a central mediator of fatty liver disease pathogenesis. This promising R&D strategy will also bring new knowledge about the disease mechanisms and improved understanding of the pathogenic process and disease drivers. To that end, mtFOIE GRAS envisages a training-through-work plan that brings together an intersectoral, multidisciplinary team of researchers and technicians experts in their fields, from basic to translational research, clinical practice, technology commercialization and public advocacy. Together with several PhD students, the team will share expertises and work synergistically along the value creation chain to address the unmet medical need of more informative NAFLD assessment. In the process, mtFOIE GRAS will endow the involved staff with excellent scientific knowledge and transferable skills while building and strengthening intersectoral cooperation among partners, thus contributing to EU RD&I excellence.

PAS GRAS aims to prevent and reverse obesity and associated metabolic complications in four age groups: pre-pubertal children (3-9 yr), adolescents (10-18 yr), young adults (19-25 yr), and adults (25-55). PAS GRAS focuses on four main pillars. 1) Develop a personalized risk assessment tool (RAT): an algorithm that will anticipate obesity priming and development in the critical age groups, and identify risk factors for specific complications in subsequent years that will constitute new outcomes for interventional studies. 2) Develop and implement RAT-based personalized interventions by integrating non-pharmacological lifestyle modifications including Mediterranean Diet components alone or with rational pharmacological targeting metabolic and neuroendocrine mechanisms. 3) Inform and engage effectively target groups on obesity causes, risks and intervention by co-production of creative and interactive digital tools (including a simpler version of the RAT) and personalized diet and physical activity programs. 4) Expand and consolidate the PAS GRAS tailor-made campaign across Europe through developing joint programs for health and food/nutrition literacy and physical activity, with healthcare centres, schools, sports clubs, municipalities, and other relevant actors and public authorities. PAS GRAS outcomes will contribute to a long-term 15% decrease in overweight/obesity prevalence in adults and 30% in children/adolescents in the EU until 2050, contributing to a downstream reduction of obesity-associated complications, pharmaceutical and surgical interventions, and to promote Mediterranean Diet as tool for a more nutritious and sustainable future. PAS GRAS is a unique multi- and interdisciplinary research team from 8 countries, including 12 top-level Universities and Research Institutions. Non-academic partners include a civil organization, one company, one patient organization and one Pan-European research Society.

EDENT1FI is a unique and timely project building and operationalising an open platform for general population screening of children/adolescents for type 1 diabetes (T1D) throughout Europe. The case is compelling: T1D is a common chronic disease affecting >1 in 300 children or adolescents. Decades of European research have signposted the step-wise nature of T1D development and generated tools for early diagnosis, monitoring and disease modification. EDENT1FI now positions Europe as the leader in early interception of T1D. Our goals are to identify individuals at earlier, pre-clinical stages, dramatically reducing clinical severity at T1D diagnosis and providing the opportunity for interventions with disease modifying therapies to delay or prevent clinical T1D. Spurred by the success of our collaborations in model European childhood screening activities and clinical networks in GPPAD and INNODIA, EDENT1FI will: establish harmonised islet autoantibody surveillance programmes to screen 200,000 children/adolescents across Europe; assess the psychosocial, medical and economic impact of screening in diverse European health systems/populations including underserved families; use state of the art metabolic sensors and biomarkers to optimise monitoring schedules for early-stage (pre-clinical) T1D aligned to maximising compliance and identifying disease progression strata; design SMART trials to expedite evaluation of disease modifying therapies; and inform and educate the public, healthcare professionals, and regulatory authorities of the new paradigms in T1D diagnosis and care. To achieve this, EDENT1FI assembles academic, clinical and industry expertise in screening, clinical care, biomarkers, machine learning, population outreach, ethics, regulatory affairs and policy to accelerate evidence-based early T1D screening into regular healthcare in Europe. The success of these activities will promote early diagnosis and prevention pathways for other chronic childhood diseases.

The main objective of the Project is to create BEAMER, a disease-agnostic behavioral and adherence model for improving quality, health outcomes and cost-effectiveness of healthcare, through improving the quality of life of individuals, enhance healthcare accessibility and sustainability. The model will allow for tailoring to individual?s needs, using Real World Data captured from patients? behaviors and health system information, transforming the way healthcare stakeholders engage with patients to optimize understanding of their condition and adherence levels throughout their patient journey. BEAMER is driven by a set of Ontology, Epistemology and Methodology principles, supported by Artificial Intelligence, Natural Language Processing, and Machine Learning. BEAMER will optimize the disease-agnostic adherence model by real-life testing proof-of-concept in 18 different pilots in Norway, Spain, the Netherlands, Germany, Portugal, and Italy, including over 18,000 patients (3000 patients in each thematic area). BEAMER will be embodied in an open source European searchable database, continuously updated, validated and optimized by empirical evidence and new insights, available to all stakeholders and adaptable for future developments in healthcare. Finally, extensive efforts will be directed to develop and implement dissemination and communication activities that increase exploitation and sustainability of BEAMER.