Despite continuous advances in diagnosis and treatment, cardiovascular diseases (CVDs) remain the main cause of mortality worldwide, accounting for about a third of annual deaths. Furthermore, they greatly reduce the quality of life of cardiovascular patients, who are estimated at a staggering figure of 85 million in Europe alone (CVD Statistics report 2017). CVDs also challenge the financial stability of modern healthcare systems and have a negative impact on economic growth. In this context, researchers are currently in great need of “big data” from population and patient cohorts to extract new knowledge on CVDs, to validate new biomarkers, and to develop new treatments. However, access to data remains a substantial barrier for researchers and innovators, especially in the new regulatory context of the GDPR (Nicholas, M. et al. Information Systems Frontiers, 2019).
For a long time, cardiovascular research had been conducted based on single cohorts such as the well-known Framingham Heart Study. However, single studies are limited to specific populations, geographical areas and even data types. Consequently, multi-cohort approaches have been proposed, both in Europe and in Canada to allow researchers to investigate heterogeneous determinants and biomarkers of CVD in more comprehensive samples, and to uncover new biomedical knowledge with increased sample size, geographical coverage, and data richness. However, these initiatives did not develop the much-needed IT infrastructures to enable the re-use of the data beyond the duration of the funded projects.
The main challenges are: 1) there are no catalogues to enable easy access to information on available data, their precise characteristics and potential for cardiovascular research studies; 2) access request mechanisms remain highly traditional, manual and lengthy, which greatly reduce the efficiency in data-driven biomedical research; 3) re-usability of the data for cardiovascular personalised medicine is often reduced when the funding is terminated; 4) major ethical and legal concerns that need to be addressed to enable responsible data sharing and analysis with a high level of data protection and security.
The main objective of euCanSHare is to build a multi-centre big data platform for cardiovascular research that addresses the challenges listed above. This user-friendly platform will provide several functionalities that will enable easy access to information on available data, that will facilitate the process of requesting and granting access to the data, as well as the process of building data analysis workflows to execute the research studies, while complying to the highest ethical and legal standards of data privacy and security.
