HARMONIA will leverage existing tools, services and novel technologies to deliver an integrated resilience assessment platform working on top of GEOSS, seeing the current lack of a dedicated process of understanding and quantifying Climate Change (CC) effects on urban areas using Satellite and auxiliary data available on GEOSS, DIAS, urban TEP, GEP etc. platforms. HARMONIA will focus on a solution for climate applications supporting adaptation and mitigation measures of the Paris Agreement. HARMONIA will test modern Remote Sensing tools and 3D-4D monitoring, Machine Learning/Deep Learning techniques and develop a modular scalable data-driven multi-layer urban areas observation information knowledge base, using Satellite data time series, spatial information and auxiliary data, in-situ observing systems, which will integrate detailed information on local level of neighborhoods/building blocks. HARMONIA focuses on two pillars: a) Natural and manmade hazards intensified by CC: urban flooding, soil degradation and geo-hazards (landslides, earthquake, ground deformation) and b) Manmade hazards: heat islands, urban heat fluxes, Air Quality, Gas emissions. Sustainable reconstruction of urban areas and the health of humans and ecosystems, are top priorities. HARMONIA will take into account the local ecosystems of European urban areas, following an integrated and sustainable approach by incorporating the active communities’ participation initiative, which will involve the use of a social platform. Paying extra attention to Sustainable Urban Development, one of the Societal Benefit Areas posits that use of EO is a crucial tool towards resilient cities and the assessment of urban footprints, to promote equity, welfare and shared prosperity for all, feed new indicators for the monitoring of progress towards the Sustainable Development Goals in an EU context.

COVID-X will bridge the collaboration divide between eHealth solution providers -with emphasis on lean startups and small and medium-sized enterprises (SMEs)-, and the healthcare professional system to fight COVID-19. The purpose is to boost an end-to-end agile validation programme of cutting-edge technology in three real-world clinical scenarios, located in hotspots of the pandemic: Italy, Spain and Sweden. The project will fast-track value streams between the two poles under consideration: 1) attract, invest and empower a community of European eHealth SMEs –the beneficiaries of an acceleration program, selected by open calls- that will provide market-ready fast, cost-effective and easily deployable sampling, screening, diagnostic and prognostic systems and/or data-driven services and tools, already certified with -or close to receive- the CE marking (type 1 of the call); 2) actively involve some of the most relevant hospitals of Europe that have the resources, critical mass and ambition to scale-up their capabilities in the COVID-19 response; thanks to the support of an innovative data sandbox, released as an in-house asset of COVID-X, to facilitate access easily, uniformly and securely to various health data sources, and providing data services including Artificial Intelligence (AI)-based decision support systems, data security, visual analytics and intuitive dashboards capabilities. The project will invest dedicated efforts to enforce data privacy and security, ethical compliance and user acceptance. Besides a solid consortium to access world class startups/SMEs, deliver highly valuable technological & business services, provide an innovative data Sandbox with AI capabilities for COVID related services and access 3 piloting sites, COVID-X targets to attract +155 applications and select 31 to undertake through the COVID-X Programme, investing a total of €4.0mil in high impact solution providers.

Fibrostenosis is the driving reason for the persistent need in bowel resections in inflammatory bowel diseases (IBD). Current IBD therapies are limited to solely targeting inflammation. While these therapies in some, but not all, cases lead to symptomatic disease remission, recurrent flares interspaced with periods of remission will still result in cumulative gut wall remodeling and fibrosis. Indeed, despite these therapeutic strategies to control inflammation, fibrostenosis incidence and bowel surgical resection is not declining in IBD patients, as no anti-fibrotic drugs are currently available. The aim of this project is to validate fibroblast therapeutic targets for preventing and/or treating fibrosis in IBD-patient-samples with an emphasis on C3 and/or Tyk2/STAT3 and/or NLRP3 in the evolution of intestinal fibrosis. The anti-fibrotic efficacy and mode of action of these novel immunotherapies will be studied preclinically in IBD-patient derived samples and validated in animal models of chronic colitis. In parallel, we aim to develop and validate a clinical diagnostic and prognostic pathway for fibrosis in IBD patients based on the use of non-invasive cross-sectional imaging techniques such as magnetic resonance enterography with elastography and optoacoustic. These results together will allow to design a first-in-human proof of concept randomized trial of immunotherapeutic drugs targeting complement C3 and/or Tyk2/STAT3 and/or NLRP3 pathways in intestinal fibrostenosis. Our aim is to obtain patients and regulatory approval for implementation of these novel non-invasive imaging modalities as diagnostic and prognostic tools for fibrotic IBD to allow vital future therapeutic development for intestinal fibrosis. By providing better molecular and clinical stratification of IBD patients at risk for fibrosis and by identifying and validating novel targets for anti-fibrotic therapy, we aim to pave the way in preventing and treating this invalidating IBD comorbidity.

Defining the molecular mechanisms governing memory T cell differentiation and homeostasis is of pivotal importance to generate durable and protective T cell responses against infections and cancers. Considerable knowledge in this regard has been acquired in mouse models but is still limited about human T cells. In particular, some mechanisms are assumed to occur in humans but were never formally demonstrated. We showed that memory T cells adoptively-transferred with bone marrow transplantation failed to persist in recipient hosts in the absence of antigen. By contrast, self/tumor-specific naïve T cells rapidly acquired T memory stem cell (TSCM) attributes and subsequently reconstituted the memory T cell pool by homeostatic differentiation. Current models indicate human TSCM cells as superior to conventional memory T cells in regards to effector potential and persistence capacity. Genome-wide expression analysis identified candidate TSCM cell-specific transcriptional regulators that were shown to inhibit senescence, promote self-renewal and regulate somatic differentiation. In this project, by using single cell technologies, primary human samples and in vivo humanized models, we will define the molecular mechanisms at the basis of memory T cell formation and maintenance in humans. We will initially define the antigenic requirement for the long-term persistence of memory T cells by following the fate of adoptively-transferred T cells. As the field remains unexplored, we will investigate the acquisition of memory attributes by self/tumor-specific T cells on multiple functional levels. The gene products specifically expressed by self-renewing TSCM cells will be finally tested for their capability to arrest T cell differentiation and generate long-lived memory T cells with enhanced stem cell-like properties. Our results will impact multiple physiological and pathological situations involving T cell-mediated immune responses.

SYNTHIA is an ambitious collaboration between public and private institutions to facilitate the responsible use of Synthetic Data (SD) in healthcare applications. The project will improve the methodological and technical aspects of SD Generation (SDG) by developing new techniques and advancing established ones for different data modalities, including genomics and imaging, to improve the generation of realistic multimodal and longitudinal data. This project will provide the research community with approaches for transparent benchmarking of alternative SDG methods for specific applications, identify and establish evaluation metrics and methodologies, and contribute to the standardisation of an evaluation assessment framework for SD. Robust evidence of SD applicability in a set of use cases across a broad spectrum of medical conditions will be crucial to demonstrate the potential of SD to accelerate data-driven solutions of equivalent quality to those derived from real patient data. Furthermore, legal and regulatory implications of SD use will be analysed with the aim of delivering an assurance framework to guide secure SD utilization in healthcare. These significant breakthroughs will be implemented through the open SYNTHIA federated platform, facilitating responsible SD use by the health research community. The platform will facilitate users´ long-term access to extensively validated, reusable synthetic datasets, as well as to SDG workflows and SD assessment frameworks. The federated infrastructure will rely on extended open-source frameworks for interoperability with other data-sharing infrastructures in the context of the European Health Data Space. A multidisciplinary collaboration of SDG developers, FAIR data experts, clinical researchers, developers of therapies and data-based tools, legal experts, socio-economic analysts, regulatory, policy advocacy, and communication experts will provide a 360º vision on how to advance healthcare applications through SD use.