About 10% of all decedents in the population die after admission to an intensive care unit (ICU). These patients often have distressing symptoms and may receive more intense life-prolonging treatment than they would have chosen, their family members often experience lasting distress from the experience and many ICU physicians and nurses are burdened by their perception of potentially non-beneficial care. The EPIC project aims to sustainably improve palliative care for critically ill patients and their families in the ICU. An interdisciplinary consortium collaborates to provide a novel harmonized palliative care practice model using telemedicine. The project is the first European interventional study on palliative care in the ICU, using a systems-based approach with proactive patient identification, checklist and blended learning targeted to specific requirements of ICU clinicians. Effectiveness of the new model is assessed through a stepped wedge randomized trial with 7 clinical centers from 5 European countries, 23 multi-disciplinary ICUs and enrolment of 2001 patients. Primary outcome is a reduction in ICU stay to relieve suffering. Cost implications and cost effectiveness will be assessed from different perspectives. An evidence-based patient decision aid for critically ill patients is developed. Additional outcomes serve deepen our understanding of barriers and facilitators and provide ethical recommendations for the use of telepalliative care in civic society. The vision of EPIC is to contribute to a mind shift from a narrow focus on prolonging life towards more holistic care. A European patient and family advisory group is implemented to engage patients and family members from the start and co-create open-access information to increase acceptance of palliative care. Telemedicine offers a low-cost solution to spread the model to all regions in Europe and open new avenues for patient-centered care.

Recent evidence demonstrates that cancer is overtaking cardiovascular disease as the number one cause of mortality in Europe. This is largely due to the lack of preventative measures for common (e.g. breast) or highly fatal (e.g. ovarian) human cancers. Most cancers are multifactorial in origin. The core hypothesis of this research programme is that the extremely high risk of BRCA1/2 germline mutation carriers to develop breast and ovarian cancer is a net consequence of cell-autonomous (direct effect of BRCA mutation in cells at risk) and cell non-autonomous (produced in distant organs and affecting organs at risk) factors which both trigger epigenetic, cancer-initiating effects. The project’s aims are centered around the principles of systems medicine and built on a large cohort of BRCA mutation carriers and controls who will be offered newly established cancer screening programmes. We will uncover how ‘cell non-autonomous’ factors work, provide detail on the epigenetic changes in at-risk tissues and investigate whether these changes are mechanistically linked to cancer, study whether we can neutralise this process and measure success in the organs at risk, and ideally in easy to access samples such as blood, buccal and cervical cells. In my Department for Women’s Cancer we have assembled a powerful interdisciplinary team including computational biologists, functionalists, immunologists and clinician scientists linked to leading patient advocacy groups which is extremely well placed to lead this pioneering project to develop the fundamental understanding of cancer development in women with BRCA mutations. To reset the epigenome, re-establishing normal cell identity and consequently reducing cancer risk without the need for surgery and being able to monitor the efficacy using multicellular epigenetic outcome predictors will be a major scientific and medical breakthrough and possibly applicable to other chronic diseases.

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.

Multiple sclerosis (MS) is a devastating immune-mediated disorder of the central nervous system. Since there is no cure available yet for MS, the primary therapeutic goal for MS patients is to slow down disability progression and to reduce relapses at early stages of the disease. Despite 19 available disease modifying treatments (DMTs), the large heterogeneity of the disease, further complicated by the high prevalance of comorbidities and multipharmacy, and the limited understanding of the working mechanisms DMT thereon results in a poor and variable treatment response in a real-world setting. The CLAIMS project is a public-private partnership aiming to address this and make precision medicine for MS patients a reality through data-driven prognosis and treatment advice, in order to better slow down disease progression and eventually conversion to progressive MS. We will develop, validate and submit for regulatory approval a companion diagnostic platform, which offers the MS care team a holistic view of the patient through the visualization of the clinical and subclinical biomarkers and the prediction of the expected disease trajectory under different treatments. For biomarker extraction and treatment prediction, state-of-the-art technologies that allow a reliable and scalable implementation across the world will be used. We believe this platform will initiate the paradigm shift from a trial-and-error, experienced-based treatment of MS patients to a first-time-right, value-based holistic treatment management, and will, hence, improve patient outcomes at a lower total cost of care, enhance patient experience and improve the well-being of the care team.

Ovarian cancer (OC) is the most lethal of female cancers, often termed a “silent killer”. DISARM’s overall approach to tackle the significant gaps in hereditary OC management lies in tackling both key elements of risk assessment and early detection. The project will investigate multifactorial risk assessment versus standard practices in 4 EU Member States (MS) (Lithuania, Portugal, Czech Republic, and Greece), and will upscale and validate a set of easy-to-use, highly accurate and affordable technologies in five countries (UK, Lithuania, Portugal, Czech Republic, and Greece). Several intelligent digital assets will optimally support and enhance our clinical studies, while a range of multifaceted activities will ensure the future uptake and adoption of DISARM solutions. The project aligns with the Innovation Action character of this topic by focusing on both mature technologies that can be upscaled in routine healthcare and on emerging technologies that have already shown a potential to justify larger scale validation activities. Our ultimate ambition is to holistically investigate the preconditions and set the stage for rolling out proven solutions in routine OC risk assessment, and in parallel to create further evidence for the introduction of novel promising elements in early detection programmes. DISARM gathers 26 partners from 12 countries (10 EU MS, the UK and Canada), thereby exhibiting a significant geographic coverage, strengthening European and international collaboration and ensuring widespread diffusion of the project results. This action is part of the Cancer Mission cluster of projects on ‘Prevention and Early Detection (early detection heritable cancers)