BACKGROUND:In an unprecedented rate data in the life sciences is generated and stored in many different databases. An ever increasing part of this data is human health data and therefore falls under data protected by legal regulations. As part of the BioMedBridges project, which created infrastructures that connect more than 10 ESFRI research infrastructures (RI), the legal and ethical prerequisites of data sharing were examined employing a novel and pragmatic approach.METHODS:We employed concepts from computer science to create legal requirement clusters that enable legal interoperability between databases for the areas of data protection, data security, Intellectual Property (IP) and security of biosample data. We analysed and extracted access rules and constraints from all data providers (databases) involved in the building of data bridges covering many of Europe's most important databases. These requirement clusters were applied to five usage scenarios representing the data flow in different data bridges: Image bridge, Phenotype data bridge, Personalised medicine data bridge, Structural data bridge, and Biosample data bridge. A matrix was built to relate the important concepts from data protection regulations (e.g. pseudonymisation, identifyability, access control, consent management) with the results of the requirement clusters. An interactive user interface for querying the matrix for requirements necessary for compliant data sharing was created.RESULTS:To guide researchers without the need for legal expert knowledge through legal requirements, an interactive tool, the Legal Assessment Tool (LAT), was developed. LAT provides researchers interactively with a selection process to characterise the involved types of data and databases and provides suitable requirements and recommendations for concrete data access and sharing situations. The results provided by LAT are based on an analysis of the data access and sharing conditions for different kinds of data of major databases in Europe.CONCLUSIONS:Data sharing for research purposes must be opened for human health data and LAT is one of the means to achieve this aim. In summary, LAT provides requirements in an interactive way for compliant data access and sharing with appropriate safeguards, restrictions and responsibilities by introducing a culture of responsibility and data governance when dealing with human data.

Usability testing methods are nowadays integrated into the design and development of health-care software, and the need for usability in health-care information technology (IT) is widely accepted by clinicians and researchers. Usability assessment starts with the identification of specific objectives that need to be tested and continues with the definition of evaluation criteria and monitoring procedures before usability tests are performed to assess the quality of all services and tasks. Such a process is implemented in the p-medicine environment and gives feedback iteratively to all software developers in the project. GCP (good clinical practice) criteria require additional usability testing of the software. For the p-medicine project (www.p-medicine.eu), an extended usability concept (EUC) was developed. The EUC covers topics like ease of use, likeability, and usefulness, usability in trial centres characterised by a mixed care and research environment and by extreme time constraints, confidentiality, use of source documents, standard operating procedures (SOA), and quality control during data handling to ensure that all data are reliable and have been processed correctly in terms of accuracy, completeness, legibility, consistence, and timeliness. Here, we describe the p-medicine EUC, focusing on two of the many key tools: ObTiMA and the Ontology Annotator (OA).

Personalized medicine seems to be a potential solution to the known challenges facing clinical research and drug development. However, the personalized approach requires many new software tools that are able to interact with each other. These applications are often developed by academic groups as part of a research project. To be employed in clinical trials, these tools must undergo a process called computer system validation (CSV) for compliance with Good Clinical Practice (GCP), regulatory and ethical requirements. Four academic developer groups of the EU project p-medicine (www.p-medicine.eu) were interviewed to evaluate the readiness of their developed products to be used for clinical research in a regulated environment. An analysis of the survey results showed that considerable gaps exist in tool maintenance, quality management and compliance documentation. Because all developer groups use agile development methods, recommendations for agile quality assurance usable in academic groups and a concept of “compliance by design” were developed to enhance quality management, prepare tool development for computer system validation and usage in clinical trials.