3TR is a transdisciplinary consortium made of experts in all areas of medicine, basic sciences and bioinformatics from academic institutions, SMEs, and 8 major pharmaceutical companies, teamed to study a fundamental issue in medicine: the mechanisms of response and non-response to therapies, the major aim of 3TR, both within single disease entities and across diseases, where molecular stratification may identify shared disease taxonomies. The molecular identification of groups of patients to whom a drug will benefit, will allow focusing on those who are drug orphan. Harmonization of data from existing academy or industry-sponsored studies will identify biomarkers to inform a new collection. Specimens of diseased tissues, blood, stools, and other fluids will be obtained in a de novo observational prospective trial with standard of care medication prior, during and after first or second line of treatment. Because the studies will be at different phases of progression, a carrousel model of work was designed for input and output of data to be continuously analysed, and interpreted, to inform those measurements to be undertaken and allow cross-validation of results. The 3TR team will elucidate the role of the microbiome, genetics and regulatory genomic features in disease progression. The working aims of 3TR are: 1) establish a centralized data management platform; 2) perform comprehensive molecular and clinical characterisation of a prospective patient cohort; 3) establish integrated analysis of all data using advanced bioinformatics/statistical and modelling methods; 4) identify sets of predictive biomarkers of response/non-response to therapies; 5) improve the competitiveness of European industry and support development of novel solutions. 3TR will sustain beyond the project end the samples and its knowledge base. 3TR will challenge and revolutionize the conventional single-disease based approach with important implications in future disease treatment.

Exposures at the workplace contribute to many non-communicable diseases (NCDs) with a similar magnitude as urban air pollution or obesity. Given the associated societal and economic (2-6% GDP) pressure, ensuring a healthy work environment is a strategic goal for the European Commission. Demographic changes (aging workforce, female workers) and the rapidly changing nature of work with respect to secure employment and migration, are posing additional challenges. We define the working-life exposome as all occupational and related non-occupational factors (general and socio-economic environment, lifestyle, behaviour). Taking a working-life exposome approach will help address these challenges by providing better insights in how complex working-life exposures are related to NCDs, for vulnerable groups (female, migrant, insecure job workers) or life stages. The working-life exposome is in its infancy and new approaches and methods are needed. In EPHOR a consortium of exposure, health and data scientists and technology developers will develop a working-life exposome toolbox, with stakeholder involvement. The toolbox will make available to scientists, policy makers and occupational health practitioners: 1) innovative methods for collection, storage, and interpretation of more complete and individual level working life exposome data; 2) better knowledge on how the working life exposome relates to NCDs, including complex interactions, vulnerability, biological pathways and early signs of health damage, by uniquely combining large-scale pooling of existing cohorts with focused case studies; 3) models for assessing the economic and societal impact of working life exposures. EPHOR will lay the groundwork for evidence-based and cost-effective preventive actions to reduce the burden of NCDs as a result of the working-life exposome. Thereby, health, wellbeing and productivity of the EU population will be improved and the burden on the EU health care systems reduced. EPHOR is part of the European Human Exposome Network comprised of 9 projects selected from this same call.

In this project, a multinational consortium of high-tech SMEs, academic research institutes, biotech and pharma partners, affiliated patient-centred organisations and professional societies will achieve a multi-faceted diagnostic and prognostic platform and a precision medicine approach. This consortium will together realize a patient empowerment centred decision support system that will enable multiple stakeholders to participate in improved and more rapid diagnosis and prognosis, as well as the potential of precision medicine for accelerated development of new therapies. Citizens and patients will be empowered to contribute to the efficient planning and usage of resources. The project will begin by rapidly delivering a nomogram. Data from the pandemic will be used to validate and further optimise a scalable multifactorial diagnosis/prognosis solution. Existing and new data and sample collection efforts will be used to perform molecular profiling, which - using advanced AI techniques will be shaped into a precision medicine approach. These initial outputs will undergo further enhancement and assessment to evaluate the value they add to the development of a decision support system. The entire effort will be supported by the deployment of a federated machine learning system that will allow for the GDPR compliant use of multinational data resources. The various iterations of the decision support system and the federated machine learning system will be made available to other coronavirus initiatives with the intent to develop a stakeholder community that forms the basis for a highly efficient innovation ecosystem. Our proposed study will be one of the first to develop innovative machine learning, and clinical procedure improvement that will potentially make a huge socio-economic impact for the coronavirus outbreak.