PALLIAKID is an interdisciplinary project aiming to evaluate the feasibility, effectiveness, and cost-effectiveness of novel interventions for children, adolescents and young people (AYA) with palliative and end-of--life care needs in different healthcare systems across Europe, with a focus on those factors that influences the active patients' and family caregivers' engagement. PALLIAKID responds to several needs or gaps identified by the consortium clinical partners, grouped into three cornerstones of paediatric palliative care: 1) Early identification of children and AYAs with palliative and end-of-life care needs, 2) Comprehensive assessment of children and their family caregivers' needs, 3) A comprehensive, personalised, interdisciplinary care plan including Advance Care Planning. The proposed solution entails three main results: PALLIAKID Eary Detection System, PALLIAKID intervention (Needs assessment, Advance Care Planning and Patient Journey digital platform); and PALLIAKID XR-based capacity-building program for professionals. In addition, the project will develop policy recommendations, guidelines and standards for patient-centred communication, together with a scale-up strategy to guarantee the project result's’ sustainability and impact. In this sense, PALLIAKID aims to reduce taboos and misunderstandings of paediatric palliative care with its activities and the planned Public Engagement Strategy. The consortium is composed of 19 entities with the needed and complementary expertise and knowledge to respond to the proposed objectives, including the triad perspective (child-family-professional): five clinical sites to co-design and test the PALLIAKID solutions, two European networks, four experts in the needs assessment and ACP tools to be adapted (HexCom and IMPACT), three technological partners, one expert in evaluation, three experts in SSH and one expert in data and ethical issues.

Cross-border collaboration can tackle the challenges in accessing relevant health data essential for international collaboration between scientists and clinicians, researchers, and health industry. Privacy concerns and regulations on personal data have made the sharing of health data increasingly complex and time-consuming for data controllers, thus severely limiting the access of SMEs, researchers, and innovators to health data. Further complications in cross-border collaboration arise from differences in interpreting the EU GDPR, national regulations, and heterogenous and changing data permit processes at hospital sites. The PHEMS project will provide European children’s hospitals with a decentralized and open health data ecosystem concept consisting of technical components and governance frameworks. The objective is to facilitate access to health data, advance federated health data analysis and build services for the on-demand generation of shareable, synthetized, and anonymized datasets. To achieve this, the project will focus on bridging the gaps in data access and use, especially in the integration of ethical, legal, and technical requirements, including the responsibilities of data controllers and the rights of data subjects. This will allow health data controllers to engage in collaboration without losing control on compliance with respect to GDPR, national legislation or internal policies of their organization. The techniques and tools for generating algorithmically anonymized and synthetic datasets will undergo robust validation processes through three clinical use cases conducted by the European Children’s Hospitals Organisation (ECHO) community. The goal is to assess the usage of custom-generated synthetic data with real-life questions. Data users, such as researchers, SMEs, innovators and the pharmaceutical and MedTech industry, will be engaged through community building, hackathons, and interaction with relevant European large-scale initiatives.

The European Rare Diseases Research Alliance (ERDERA) aims to improve the health and well-being of the 30 million people living with a rare disease in Europe, by making Europe a world leader in Rare Disease (RD) research and innovation, to support concrete health benefits to rare disease patients, through better prevention, diagnosis and treatment. This Partnership will deliver a RD ecosystem that builds on the successes of previous programmes by supporting robust patient need-led research, developing new diagnostic methods and pathways, spearheading the digital transformational change connecting the dots between care, patient data and research, while ensuring strong alignment of strategies in RD research across countries and regions. Structuring goal-oriented public-private collaborations targeted at interventions all along the R&D value chain will ensure that the journey from knowledge to patient impact is expedited, thereby optimising EU innovation potential in RD. To support its ambition and missions ERDERA has been designed as a comprehensive and integrated ecosystem of which structure can be compared to an institute encompassing three main parts: (i) funding, (ii) internal (in house) Clinical Research Network that implements research activities targeting clinical trial readiness of RDs and accelerating diagnosis and translation of research discovery into improved patient care, and (iii) related supporting services (Data, Expertise, Education and Training) as well as an acceleration hub that serve external and internal RD community, all supported by all-embracing coordination and strategy and foundational (inter)national alignment.

Our overall objectives are to accelerate the diagnosis, and enable personalised management, of inherited metabolic diseases (IMDs). Established academic technology for statistical genomic analysis, deep learning-based prediction of protein structure, and whole-body metabolic network modelling shall be applied to generate personalised computational models, given patient-derived genomic, transcriptomic, proteomic and metabolomic data. To train diagnostic models, a comprehensive clinical team will recruit 1,945 diagnosed patients with a wide variety of IMDs, then validate the clinical utility of personalised computational models on a set of 685 undiagnosed patients. An enhanced human metabolic network reconstruction, especially for lipid metabolism, reaction kinetics and inherited metabolic disease pathways, will increase the predictive capacity of cellular and whole-body metabolic network models. As an exemplar for other IMDs, personalised computational modelling will be used to identify compensatory and aggravating mechanisms that associate with clinical severity in Gaucher disease. The predictive capacity of personalised models will be validated by comparison with additional empirical investigations of protein structure and function as well as metabolomics, tracer-based metabolomics and proteomics of patient-derived in vitro disease models. To maximise the potential for impact, personalised modelling software will be developed to be generally applicable to a broad variety of IMDs, and implemented in a way that is both accessible to clinicians and admissible to regulatory authorities. Sustainability will be promoted by development of a roadmap for a European foundation to aid personalised diagnosis and management of IMDs, informed by broad stakeholder consultation. This is a unique opportunity to realise the potential of personalised computational modelling for a broad set of rare diseases, which is a field where European collaboration is an essential for progress.