Coronavirus disease 2019 (COVID-19) caused by infection with SARS coronavirus 2 (SARS-CoV-2) has reached pandemic proportions with more than 7 million people infected and 0.4 million people killed worldwide. Death rates are accentuated by cardiovascular comorbidities and arrhythmias leading to unexpected major cardiovascular events. Being able to identify COVID-19 patients at risk of developing cardiovascular events leading to death would allow improving surveillance and care. Currently, there is no accurate method to predict outcome of COVID-19 patients. COVIRNA is a patient-centered Innovation Action aiming to satisfy this urgent and unmet need. COVIRNA will complete and deploy a prognostic system based on cardiovascular biomarkers of COVID-19 clinical outcomes combined with digital tools and artificial intelligence analytics (i.e. prediction model). Complementary expertise of 15 EU partners from the healthcare sector, academia, association and industry will allow conducting a large retrospective study on existing cohorts of COVID-19 patients. By upscaling the already validated and patented research use only FIMICS panel of cardiac-enriched long noncoding RNA biomarkers into an in-vitro diagnostic test (COVIRNA) adapted to COVID-19 patients, the project will quickly deliver a minimally-invasive, simple yet robust and affordable prognosis tool that can be used in the context of the current COVID-19 crisis as well as in further major health issues. By tackling the cardiovascular complications in COVID-19, known to contribute significantly to mortality, the project outputs are expected to have a major impact on the pandemic outcomes. The COVIRNA test will be CE-marked and prepared for commercialization, allowing to risk stratify patients, adapt therapies and to inform drug design.

In European Union approximately 5 million people suffer from psychotic disorders. Between 30-50% can be considered resistant to treatment, and 10-20% ultra-resistant. These patients present persistent positive symptomatology, require extensive periods of hospital care, and have a greater risk of excess mortality and multi-morbidity. In addition, a high proportion of the total cost for treating schizophrenia is spent on this population (Kennedy et al., 2013). Intervention strategies based on mHealth have demonstrated their ability to support and promote self-management-based strategies. Evidence from studies point to the importance of engaging patients actively in their own treatment. This active role helps to improve adherence to treatment, and to reduce persistent symptoms severity, relapses and hospitalizations (Mueser et al., 2002). m-RESIST aims to develop an intervention programme based on mHealth to allow patients suffering from resistant schizophrenia to self-manage their condition (resistant schizophrenia and its associated comorbidities, e.g. somatic disorders and addictions). This may facilitate acceptance and involvement of patients with their own treatment, as well as of caregivers. Moreover this programme could provide a new tool to the psychiatrist, psychologists working together with other health care professionals, to better monitor patients, through a personalised and optimised therapeutic process. m-resist will (1) develop and validate an mHealth solution aimed to reduce the severity of episodes and further complications; (2) involve and promote participation of patients and caregivers in the therapeutic process increasing the awareness of patient and caregiver about the nature of the illness and its consequences, benefits of treatment and needs for healthy habits and promoting an active and collaborative role with the medical team in the treatment decision-making procedure.

Further efforts to achieve greater efficiency in allocating healthcare resources are needed in order to guarantee the sustainability of public health systems. The exponential production of new evidence is a challenge in achieving this goal. Newly validated innovative technological tools for systematic evidence identification, evaluation, and synthesis may allow for a more efficient production of evidence to inform healthcare decisions. However, it is essential to build capacity among health care professionals to properly use these tools as well as formulate collaborative strategies to implement them. This research proposal aims to evaluate a strategy for capacity building to produce "Living Evidence" syntheses to generate integrative evidence-based products that support decision-making. Consists of three complementary projects aimed at: [WP1] producing Living Overviews of previously selected priority topics in the area of cancer and respiratory diseases integrated into the Epistemonikos-L.OVE project, an innovative initiative and platform in progress that allows to generate systematic evidence synthesis in a rigorous and efficient way, displaying it in a friendly format; [WP2] preparing and disseminating Friendly Summaries of Evidence for highly relevant questions from the prioritized health topics to inform clinicians and decision makers, following validated methods; and [WP3] updating evidence supporting recommendations in clinical practice guidelines (Living Guidelines) related with the same topics, through the development of living overviews in collaboration with two European guideline developers, and following the GRADE approach to rate the quality of evidence and generate summary of findings tables. In addition to the delivery of training, the project proposes a collaborative work strategy with different actors in the health system to carry out these actions. Information will be collected throughout the whole process to assess the efficiency of this strategy.

COMPAR-EU aims to identify, compare, and rank the most effective and cost-effective self-management interventions (SMIs) for adults in Europe within four high-priority chronic conditions: type 2 diabetes, obesity, chronic obstructive pulmonary disease, and heart failure. This project addresses an important gap in current knowledge applying network meta-analysis, an extension of meta-analysis methodology that allows multiple (rather than pairwise) comparisons of intervention effectiveness, to randomised controlled trials (RCTs) that meet the study inclusion criteria. This centralised analysis of an estimated 4000 RCTs will substantially help to overcome current problems associated with the dispersion and duplication of evidence. The work will be based on a validated taxonomy of SMIs and will prioritise outcomes from the patients’ perspective. In addition, a cost-effectiveness of the most effective SMIs will be estimated to provide insights into the economic consequences of adopting SMIs for societies, healthcare budgets, and patients. Contextual factors associated with successful interventions will also be studied. Drawing on our results, we will develop and pilot decision-making tools to facilitate access to evidence-based information on the most effective SMIs to key users through a user-friendly interactive platform. A multiprong strategy for exploitation of the research findings will lead to clear business cases for implementing it in different contexts within the heterogeneous EU health system. The end goal of the project is to have an impact in supporting policy-makers, guideline developers, researchers, industry, professionals and patients to make informed decisions on the identification and implementation of the most suitable SMIs, therefore contributing to the diffusion of the knowledge, healthcare sustainability and equity and promoting EU competitiveness in a globally emerging market.

The European Regimen Accelerator for Tuberculosis (ERA4TB) has the explicit goal of developing a new combination therapy to treat all forms of TB starting from ~20 leads and drug candidates provided by EFPIA. Since details of these are as yet unavailable, we will implement an agile drug development algorithm that entails profiling and portfolio construction. Profiling involves characterisation and ranking molecules in preclinical studies comprising in vitro drug combination assays, hollow fiber and single cell analysis, innovative murine and non-human primate models, PK/PD studies, combined with biomarker discovery and non-invasive NIR or PET/CT imaging to monitor disease progression and response to treatment. Modelling, simulation and artificial intelligence tools will help progress compounds from early preclinical to clinical development and to predict drug exposure, human doses and the best combinations. After extensive preclinical profiling, selected compounds will enter portfolio development for first time in human tests and phase I clinical trials in order to ensure that they are safe, well-tolerated and bioavailable with negligible drug-drug interactions. If needed, formulation studies will be conducted to improve pharmacological properties. ERA4TB has assembled the best expertise and resources available in Europe, to build a highly effective and sustainable drug development consortium with a flexible and dynamic management system to execute the profiling and portfolio strategy, aided by clearly defined go/no-go decision points. The expected outcome of ERA4TB is a series of highly active, bactericidal, orally available drugs to constitute two or more new combination regimens with treatment-shortening potential ready for Phase II clinical evaluation. These regimens will be compatible with drugs used to treat common comorbidities, such as HIV-AIDS and diabetes, and should impact UN Sustainable Development Goal 3, namely, ending TB by 2030.