AMBROSIA aims to provide the foundations for a multi-sensing future-proof Point of Care Unit for sepsis diagnosis offered by a CMOS compatible toolkit and enhanced by on-chip photonic neural network technology to provide an accurate and rapid diagnosis. AMBROSIA will be investing in the established ultra-small-footprint and elevated sensitivity of integrated plasmo-photonic sensors reinforced by the well-known on-chip slow-light effect and micro-transfer printed lasers and photodiodes on Si3N4, as well as the functional processing and classification portfolio of integrated photonic neural network engines, towards painting the landscape of the next-coming disruption in sensor evolution, tailoring them in System-in-Package prototype assemblies, with the sensors being cheap disposable pluggable modules that can rapidly and accurately diagnose sepsis at the bedside in clinical environments. AMBROSIA targets to demonstrate a Point of Care Unit incorporating: i) a switchable sensor area array, with each sensor area facilitating a pluggable, 8-channel label-free plasmo-photonic sensor for sepsis diagnosis with a sensitivity over 130.000nm/RIU and a Limit of Detection below 10-8 RIU for each interferometric sensor, ii) an embedded Si3N4 photonic neural network processing and classifying at the same time the data from at least 7 biomarkers with zero-power providing in the first minutes an accurate and rapid diagnosis for sepsis, iii) Micro-transfer printed lasers and photodetectors on chip that will drastically decrease costs of both the sensing and neural network modules, and render the sensor arrays disposable.

Foundation models represent a paradigm shift in AI, exhibiting remarkable capabilities across multiple tasks. Their true potential lies in generalizing across diverse domains and modalities, a largely untapped frontier. DVPS advances this frontier by focusing on multimodal foundation models (MMFM), aiming to harness their capabilities across various application domains. DVPS emphasizes three core benefits of MMFM: label efficiency, compute reusability, and engineering efficiency. However, achieving these benefits in multimodal settings presents challenges such as modality-specific architecture and cross-modal alignment. To overcome these, DVPS aims to develop generalizable methods that work across diverse modalities and domains, creating a unified framework for MMFM development and integrating new modalities into existing models. The project focuses on generating foundational knowledge, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. DVPS also includes two "surprise domains" to drive innovation by challenging initial assumptions. Key objectives include the development of AutoDVPS, a toolkit for automated MMFM design, and the creation of DVPSBench, a benchmarking suite for evaluating MMFM across tasks and domains. DVPS aims to foster a European ecosystem for MMFM research, promoting transparency, fairness, and ethical compliance in line with European values. Through collaboration and open-source contributions, DVPS seeks to standardize and advance MMFM as a scientifically rigorous discipline.

The ISIDORe consortium, made of the capacities of European ESFRI infrastructures and coordinated networks, proposes to assemble the largest and most diverse research and service providing instrument to study infectious diseases in Europe, from structural biology to clinical trials. Giving scientists access to the whole extent of our state of the art facilities, cutting edge services, advanced equipment and expertise, in an integrated way and with a common goal, will enable or accelerate the generation of new knowledge and intervention tools to ultimately help control SARS CoV 2 in particular, and epidemic prone pathogens in general, while avoiding fragmentation and duplication among European initiatives. Such a global and interdisciplinary approach is meant to allow the implementation of user projects that are larger, more ambitious and more impactful than the EU supported transnational activities that the consortium is used to run. Our proposition is ambitious but achievable in a timely fashion due to the relevance and previous experience of the partners that we have gathered and that have complementary fields of expertise, which addresses the need for an interdisciplinary effort. Leveraging all these existing strengths to develop synergies will create an additional value and enhance Europe capacity for controlling emerging or re emerging and epidemic infectious diseases, starting with the COVID 19 pandemic. Such a global and coordinated approach is consistent with the recommendations of the One Health concept and necessary to make significant contributions to solving complex societal problems like epidemics and pandemics.

High-risk neuroblastoma accounts for 15% of cancer related-deaths in children. Half of the >1500 patients yearly diagnosed with neuroblastoma in the EU have high-risk disease, which will relapse or progress in half these cases after first-line treatment. Relapsed neuroblastoma is aggressive and often therapy-resistant. Monitoring for disease relapse and therapy response is crucial for the survival chance of these patients. The current standard-of-care for monitoring are imaging technologies and bone marrow assessment, which are costly, invasive and a burden for children, who often require anesthesia. These drawbacks limit how often is monitored. More sensitive, less invasive and less toxic monitoring techniques are needed. The mutational spectrum often changes in recurring tumors, which may explain therapy resistance and provide additional druggable targets. Imaging, however, provides no information about molecular characteristics. Liquid biopsy tests are minimally invasive, allow frequent sampling and sensitively detect tumor molecular markers in tumor-derived DNA and messenger RNA circulating in peripheral blood. MONALISA aims to close existing gaps and establish liquid biopsies as standard-of-care to monitor relapsed/refractory neuroblastoma, as a blueprint for other pediatric cancers. Reliable, early assessment of molecular progression or relapse is the main aim of the pragmatic randomized clinical trial proposed in MONALISA. We develop a digital decision support tool to help oncologists use the new monitoring and apply patient-reported outcomes to integrate patient viewpoints and assess the effect of minimally invasive, liquid biopsy diagnostics on quality of life. We will establish whether events can be detected earlier using liquid biopsy monitoring, and whether better overall survival is enabled by earlier diagnosis and treatment interventions. This essential step towards personalized medicine will support reliable disease monitoring under treatment. “This action is part of the Cancer Mission cluster of projects on ‘‘Diagnostics and Treatment (diagnostics).”