Modelling the integration of biobanks into healthcare systems International Biobanking Summit II: Future Directions Graz, 17 September 2013

Transcription

1 Modelling the integration of biobanks into healthcare systems International Biobanking Summit II: Future Directions Graz, 17 September 2013 Anthony J Brookes University of Leicester

2 Biobank: A comprehensive and well-organized collection of human biological samples and associated clinical and research data BIOBANKS Patient Cohort: group of subjects collected, with biosampling, for translational research or clinical trials, thereby generating clinical and research data RESEARCH HEALTHCARE

3 GEN2PHEN BioShaRE EMIF etox COPD-MAP REQUITE - Unification and utility of Genotype-to-Phenotype data - Science and IT for Biobanking - Using health data in research - Toxicology data and modelling - Systems medicine KM (COPD) - Systems medicine KM (cancer)

4 Data-to-Knowledge-for-Practice facility (DKP) in the new Cardiovascular Research Center (CRC)

5 Open access complex data Controlled access simplified inferences RESEARCH HEALTHCARE BIO-INFORMATICS ACADEMICS MED-INFORMATICS COMPANIES

6 R E S E A R C H H E A L T H C A R E

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8 Integration and Interpretation of Information for Individualised Healthcare

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10 1. STANDARDS... Semantic Standards (to allow unambiguous understanding of the data) Terminologies, Ontologies, Vocabularies, Coding systems Need cross-mapping between semantic standards, and across languages Syntactic Standards (to make data structures interoperable) Data and Metadata object models, and Exchange formats Minimal content specifications, harmonised across domains Robust core requirements, with general principles that bring flexibility Technical Standards (to build a system that works efficiently) Database models, Search systems, and User interfaces (e.g., browsers) Web-service specifications, Web 2.0 technologies ID solutions for data, databases, publications, biobanks, researchers Technologies for controlling data access and user permissions Ethical and Legal policies, implementation, and recognition-rewards structures Quality Standards (to match data to needs) measuring and representing quality in a meaningful way Important role here for metadata Recording and standardising SOPs

11 ENTITY IDENTIFIERS Data IDs - The Data Object Identifier (DOI) system, managed by DataCite. Covers a very broad concept of a data object (much more than just traditional publications). Essential for creating the web of data. Database IDs - The BioDBCore project by which database IDs can be assigned. Essential if webservices are to start connecting resources effectively. Human IDs - The Open Researcher Contributor Identifier (ORCID) system. Launched late 2013, has already issued many tens of thousands of ORCIDs. Soon to be a required author detail when submitting manuscripts. Removes ambiguity over all contributors, thereby enabling incentive/reward systems for data sharing, improved knowledge discovery options, and automation of data access control. Biobank IDs - Pilot system emerging from GEN2PHEN & BioShaRE, operated by P3G, as a basis for developing BioResource Impact Factor (BRIF) metrics. Patient IDs - Pilot system emerging from GEN2PHEN & BioShaRE, operated by P3G, as a basis for developing BioResource Impact Factor (BRIF) metrics.

12 2. CENTRAL AND/OR FEDERATED...

13 2. CENTRAL AND/OR FEDERATED... So... the degree of federation must be scaled realistically against the viability of standardizing the connections

14 3. HARMONISATION... (semantics, context dependent) Peter Robinson

15 4. QUALITY... (or at least indicate deficiences) Peter Robinson

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19 5. DATABASING... (curating, parsing, ETL) Data Creation Data Curation Data Analysis Data-Basing

20 Single Research Team Data

21 Consortium Data

22 Single Research Team Data

23 Consortium Data

24 Consortium Data

25 Consortium Data

26 Data Catalog

27 Healthcare Big Data KM 27

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32 Electronic Healthcare Records Recording Collection Models Terminology Expressiveness Precision/rigour Searchability Comparability Best Practice Search and Retrieval Models Decision Making EHR Classifications Utility Categorisation Secondary use Communication Models Registration and Location Models Information Model Structure Detail Search Storage Interoperability Notify, Find

33 Future Healthcare = Biobanking? If/When all patient data are properly under control in healthcare systems, from organisations fully engaged with a research mission, then biobanks may become largely redundant......or will they?

34 DATA SHARING...just needs the engineering?

35 metadata standards semantic standards federation standards syntax & file type standards exchange format standards query standards informed consent standards ID standards use category standards QC standards

36 Data Control

37 Data Remote Analysis

38 Data Discovery

39 Openly share the existence rather than the substance of the data.thereafter variably manage data access

40 Cafe Variome Network Collaborators UK DMuDB (with Andrew Devereau, Susan Stenhouse) Denmark diagnostic network (with Friedrik Wikman) German diagnostic network (with Arne Pfeufer) French diagnostic network (with Andre Blavier (Interactive Biosoftware)) Belgium diagnostic network (with Gert Matthijs) Canadian diagnostic network (with Forge Canada / Care4Rare) Netherlands diagnostic network (with Morris Swertz & Rolf Sijmons) Ehlers Danlos Syndrome network (with Raymond Dalgleish) Collagen disease network (with Peter Byers) Inherited Colon Cancer network (with Finlay Macrae, InSiGHT)

41 ABC tool Data Creation Data Curation Data Analysis Ethics ORCID OMICs Connect OMX-db Maelstrom Observ-OM(X) OPAL-db SORTA MICA Café Variome Data-Basing OMX Catalog DataSHIELD

42 Knowledge Sharing Recording Collection Models Terminology Expressiveness Precision/rigour Searchability Comparability Best Practice Search and Retrieval Models Decision Making...EMIF, generalising systems from EU-ADR which Classifications derive knowledge EHRs about adverse drug reactions from 30M patients in real time Utility Categorisation Secondary use Communication Models Registration and Location Models Information Model Structure Detail Search Storage Interoperability Notify, Find

43 SUMMARY Wide-ranging problem, so need to first define a precise set of input resources, starting assumptions, use cases, objectives, stakeholder roles, and expectations you want to address Even then, there could be many different, equally effective models for building, governing and sustaining an effective ecosystem Areas of diversity include: - various types and objectives of different 'biobanks - standards development, and strategies for doing this - balancing centralised and federated approaches - harmonising data semantics & data logic for combined analyses - optimising and reporting data quality and data manipulations - data curation, parsing and digitisation procedures - (big) data visualisation and (realtime) mining/use In addition to data sharing, exploit knowledge sharing, & data discovery Construct integrative domain/disease specific 'knowledge portals'

44 DKP Facility members Partners in GEN2PHEN, BioShaRE, EMIF, etox, COPD-MAP, REQUITE Anthony Brookes Bioinformatics Group Tim Beck, Charalambos Chrysostomou, Robert Hastings, Owen Lancaster, Adam Webb Sirisha Gollapudi, Robert Free, Gudmundur Thorisson The GEN2PHEN project received funding from the European Community's Seventh Framework Programme (FP7/ ) under grant agreement number The BioShaRE project received funding from the European Community's Seventh Framework Programme (FP7/ ) under grant agreement number