Multiple sclerosis (MS) is a chronic inflammatory and degenerative disease of the central nervous system (CNS). It constitutes the most common non-traumatic cause of neurological impairment among young and middle-aged people and represents a major healthcare burden. Our recent research strongly implicates infection by the Epstein-Barr virus (EBV) as the leading cause of MS, but detailed understanding of the mechanisms how EBV contributes to the disease, and whether targeting EBV could prevent or improve the course remain unresolved. To meet these challenges, we have established a consortium with extensive experience in neurology and MS, genetics, virology and EBV, epidemiology, immunology, clinical trials, artificial intelligence, as well as stakeholder involvement and responsible research and innovation (RRI). By combining this expertise, the consortium takes advantage of high-quality health registries, existing research cohorts of persons with MS, and prospective randomized clinical trials of antiviral therapies targeting the EBV infection in MS. The ambitious goals are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. By answering these questions, we would meet the challenges defined in the current call: Relationship between infections and non-communicable diseases. We would contribute with knowledge to reduce disease burden by providing the health care system with new knowledge to better understand the cause of MS, including host risk factors that influence the development of the disease. We would also provide a basis for new or improved tools to prevent MS or disease progression. Healthcare practitioners will gain access to knowledge to guide them on preventive measures and of those persons at risk of developing MS, with the ultimate goal of eradicating the disease.

Enabling integration of medical and research data, secure data sharing and leveraging responsible state-of-the-art artificial intelligence (AI)-mediated models opens immense possibilities to mitigate the impact of chronic immune-mediated diseases (CIMDs) affecting 10% of Europeans. Eight European universities, leaders in the medical and analytical field, three SMEs, one research institute and one company, at the forefront of clinical AI implementation, data infrastructure, and security, and a Patient Organisation formed the consortium WISDOM. The consortium's overarching aim is to convert complex biological information from the existing data sources into actionable insights. WISDOM builds on the premise that computational tools can provide valuable knowledge and guide decision-making at critical stages in the individual patient journey, from diagnosis to treatment initiation and optimisation. To unlock the potential of the existing data, WISDOM will address barriers of data integration and accessibility and deploy novel approaches for data processing, harmonisation, integration, and secure, trustworthy data sharing with federated access. WISDOM aims to develop computational risk stratification and outcome prediction models and tools in different CIMD use cases, building on large EU-funded multimodal datasets, and prospectively validate them on technical, clinical and user aspects to facilitate data-driven and patient-focused diagnosis, treatment, and monitoring. WISDOM aims to promote the widespread utilisation of data and facilitate responsible and critical assessment of the use of AI in healthcare using an end-user guided approach leveraging collaboration among clinicians, researchers, legal and AI experts, patient associations and rich stakeholder expertise. WISDOM’s ultimate ambition is to revolutionise the integration, management, and analysis of health data across diseases and borders to promote personalised interventions and well-being.

Multiple Sclerosis (MS) is the most frequent neuroinflammatory disease. Despite new treatments that slow the progression of the disease, patients with MS (PwMS) frequently evolve towards major disability. The pathogenesis of MS is controversially debated, but the recent discovery that infection with the Epstein-Barr virus (EBV) is a major risk factor will radically change research avenues. The BEHIND-MS consortium ambitions to understand how EBV promotes MS development. To this end, we have established a multidisciplinary team that will for the first time draw a comprehensive map of the interactions between the virus and all arms of the immune system in the blood and brain of PwMS and how they ultimately lead to neural damage, in the context of genetic risk factors. We will also develop an in vitro model of MS that integrates the virus, the immune system and brain cells reprogrammed from the blood of the same PwMS. Thus, for the first time, we will study in the laboratory the complex molecular mechanisms that give rise to MS. Finally, we will develop an animal model of prodromal MS that would be a ‘game changer’ for our understanding of MS pathogenesis and allow testing of promising new treatments. The pivotal knowledge developed in this project will empower the entire healthcare value chain to work towards better clinical management of MS. A detailed understanding of EBV-MS interactions, combined with newly identified biomarkers, and study models will open the doors for researchers, clinicians and industry to capitalize on the mechanisms underlying EBV-MS interactions, and develop new diagnostic, preventive and therapeutic tools and guidelines. Throughout the project, an open dialogue with the main stakeholder representatives will ensure a mutual understanding of patient needs and project results. Ultimately, by contributing to improved risk analysis, stratification and treatment strategies, BEHIND-MS has the potential to reduce the burden of MS on society.

The overall goal of the Big Data for Better Outcomes (BD4BO) programme is to facilitate the use of ‘big data’ to promote the development of value-based, outcomes-focused healthcare systems in Europe. To fully exploit the transformative potential of big data, consideration will need to be taken of the use of detailed personal and biological information across the spectrum of care delivery, starting from the development of innovative medicines and treatments, to market access and adoption, diffusion, and use in healthcare systems by providers and patients. This paradigm shift requires shared understanding and standards among healthcare stakeholders including patients, providers, payers, regulators, policy makers, pharmaceutical industry, and academia. OBJECTIVES The proposed Coordination and Support Action (CSA) will establish an enabling platform that brings together these stakeholder groups across the BD4BO programme to ensure quality and consistency of individual projects in line with the overarching programme objective. Our consortium therefore aims to promote the use of big Data for better Outcomes, policy Innovation and healthcare system Transformation (DO->IT). Accordingly, we will: • Define a programme strategy that ensures quality, consistency and sustainability of health outcomes related activities across individual BD4BO projects. • Integrate, synthesise, and manage knowledge from all BD4BO projects, making it easily accessible via a single knowledge exchange platform. • Act as pivotal point of collaboration, stakeholder engagement and communication for all BD4BO projects. • Provide transparency and enable the use of patient health data and human biological samples for research purposes by developing minimum data privacy standards for Informed Consent Forms (ICFs) and supporting materials for use by individual BD4BO disease-specific projects and more widely in the Research and Development (R&D) sector.

While randomized controlled trials (RCTs) remain the mainstay in drug development, approval, and reimbursement, the potential of real world data (RWD) to contribute to the understanding of drug effects is increasingly realized. Evidence, based on RWD – real world evidence (RWE) - can contribute significantly to the evidence to support decision making throughout all phases of (clinical) drug development, as well as improve efficiency in design and conduct of clinical trial programs. The aim of this project is to develop, implement and establish evidentiary standards and methods to address the data and evidentiary needs of regulatory authorities and HTA bodies towards a more efficient use of RWD for the development, registration and assessment of medicinal products in Europe (More-EUROPA).