The outcomes of BioMedBridges will lead to real and sustained improvement in the services the biomedical sciences research infrastructures offer to the research community. Data curation and sample description will be improved in all of them by the adoption of best practices and agreed standards. Many improvements will emerge from new interactions between RIs created by data linkage and networking.
The main benefit of integration however comes to all the infrastructures and all of Europe’s scientists. By creating an environment that allows data and service exchange in the biological and medical sciences, we will empower scientific research and its translation into industry, the clinic and the environment, to address the grand challenges Europe faces in the 21st century.
BBMRI—Modern clinical research will be significantly supported by linking large collections of high quality, well documented samples from humans and model organisms. By integrating data from biobanks and molecular research, and by improving access to metadata, the descriptions and therefore discoverability of biomedical samples will be hugely improved.
|EATRIS—In personalised medicine, decisions about treatment options will be supported by access to integrated data and information from multiple reference resources and analysis platforms.|
|ECRIN—Data relevant to personalised medicine that is generated by the different research infrastructures will be made available to scientists and clinicians in an ethical, robust and sustainable manner, and mechanisms of interoperability for different data types will be developed. Clinical trial data, biomolecular data and basic research data will be better linked.|
|ELIXIR—New discoveries will be facilitated by revealing possible connections between linked and accessible biomolecular, clinical, biobank (tissue sample) and image data.|
Infrafrontier—The mouse is an important model organism for studying human disease. Harmonising ontological descriptions of phenotype in mouse and human and improving links between mouse model data and human data, using diabetes and obesity as examples, will increase the relevance of data that is generated in mouse studies for clinical studies.
|Instruct—Structural data on biomolecules will be linked with clinical data, maximising its value by enabling its use in studies of important biological and medical problems.|
|ERINHA—Strains of known species and unknown species of pathogens will be more easily distinguished and accurately identified by linking to biomolecular data. This is important in controlling epidemics and in security applications.|
|EU-OPENSCREEN—The enormous effort involved in high throughput screening for chemical tools and drugs will be supported by building targeted strategies based on integrated clinical, cheminformatic, and biomolecular data.|
|EMBRC—Links to metagenomics data will help characterise poorly understood ecosystems and cheminformatics data to characterise the activity of isolated natural products.|
Euro-BioImaging—Extensive image data sets representing different biological scales spanning biomolecules, cells, tissues and organisms will be linked, enabling drug-target and biomarker discovery for human disease.