EATRIS data challenges!
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- Rosalyn Manning
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1 EATRIS data challenges!! e-infrastructure workshop! Jan-Willem Boiten - CTMM! Hinxton; May 15 th 2014!
2 EATRIS positioning! Vision! Making translation of scientific discoveries into medical products more effective to improve human health and quality of life.!! Mission! To support researchers in developing their biomedical discoveries for novel preventive, diagnostic or therapeutic products up to clinical proof of concept.!! Supporting academia, funders, SME & biotech/pharma!!
3 Components of the translational path! Academia Research /chari4es SME/biotech Pharma Client projects Infrastructure GMP manufacturing Licenses Imaging facili4es Biobanks Clinical trial units Pa4ent groups Nat l governments Regional dev. Funds H2020 Venture capital Pharma partnering Funding Exper7se Clinicians Latest technologies Project management Regulatory Partnering
4 EATRIS: archeologists of biomedical research! X AREAL SURVEY DEEP EXCAVATION PaTern Recogni4on in Open Data and detailed Excava4on should be separated
5 Typical EATRIS IT processes! Secure, mul7center acquisi7on, processing and sharing of high- quality clinical data Secure & efficient de- iden7fica7on and sharing of clinical images Secure, mul7center biosample logis7cs Translational workbench for integration, browsing & analysis of project data Efficient crea7on, analysis, and dissemina7on of molecular biology data Common foundation: compute services, data storage & archival, ethical & legal procedures, data security/protection, secure data transfer, etc.
6 Some aspects are quite typical to EATRIS! Secure, mul7center acquisi7on, processing and sharing of high- quality clinical data Secure & efficient de- iden7fica7on and sharing of clinical images Secure, mul7center biosample logis7cs Translational workbench for integration, browsing & analysis of data Efficient crea7on, analysis and dissemina7on of molecular biology data Common foundation: compute services, data storage & archival, ethical & legal procedures, data security/protection, secure data transfer, etc.
7 but also many problems are shared! Secure, mul7center acquisi7on, processing and sharing of high- quality clinical data Secure & efficient de- iden7fica7on and sharing of clinical images Secure, mul7center biosample logis7cs Translational workbench for integration, browsing & analysis of data Efficient crea7on, analysis and dissemina7on of molecular biology data Common foundation: compute services, data storage & archival, ethical & legal procedures, data security/protection, secure data transfer, etc.
8 Specific EATRIS IT challenges! Secure & efficient multi-center data sharing in compliance with all EU, national, and local regulations (patient data & ip protection)! Harmonization and pooling of heterogeneous data sets created with various local standards (translational workbench)! Maintain and raise data processing quality standards as required for clinical research (deep excavation view on biomedical data)! Social engineering: create a culture of collaboration and data sharing between translational scientists! Give clinical domain experts direct access to complex molecular biology results in a meaningful manner! Key words: quality, security, social engineering, data sharing, i.e. professional research IT
9 Generic EATRIS data challenges! Large data sets: clinical images and DNA,RNA, and protein data sets: storage and (secure) transfer issues! Data processing issues: compute for image processing, DNA/ RNA sequencing processing pipelines! Samples are often quite unique (e.g. tumor samples); data cannot easily be re-generated. Data storage is therefore crucial.! EATRIS is an European network of collaborating expert centers; data are therefore produced in a very distributed manner! Anticipated growth is phenomenal: sequencing will become the method of choice in cancer research (and other domains)! Data is typically secure, but needs to be accessible to project partners across the continent! Ø Accessible, but not open data!
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