An overview of modern institutional bio-banking and the relevance of bio-banking informatics specifications.

1. Informatics Principles of Modern
Institutional Bio-banking:
The Road Ahead
Michael Hogarth, MD
Medical Director, Clinical Registries
Professor, Internal Medicine
Professor, Pathology/Lab Medicine
UC Davis Health System
michael.hogarth@ucdmc.ucdavis.edu
http://www.hogarth.org

2. Biobanking
• Biobanking is a process involving the collection of a wide
array of biospecimens including blood, saliva, plasma,
and tissue
• Biobanking is a powerful resource for biomedical research

3. Is it important?
Time Magazine March 23, 2009 and Time Magazine November 25, 2009

4. Biobanking Requires
• Consenting processes
• Collection services
• Storage infrastructure
• Specimen Access and
Distribution
• Accounting
• Regulatory compliance
• Information Management to
support these functions

5. Biobanking Information Management
System ‘state-of-the-art’ .... Excel!!

6. Current State of
Biobanking Information Management
• Informatics consists of few enterprise systems
and many using excel spreadsheets and MS
Access as well as ‘custom in-house programs’
• Biobank data is in silos even within institutions
• Federated online searching across different biobanks is
nearly impossible
• A lack of common “information management
practices”
• Lack of standards – no standard data model, no
standard data elements
• No interoperability between biobanking information
systems or externally with EHR or other systems

7. Biobanking Informatics -- Integration
• Biobanks have limited value as stand-alone systems
• Biobanks and “interoperating” with other systems
• Other biobanking systems (data sharing, federated searching)
• Disease Registries (and clinical data repositories)
• Storage/preservation systems (“smart freezers”)
• Clinical Trials Management System (CTMS)
• Pathology whole slide imaging repository
• Genomic data repository (ie, caARRAY)
• Financial management system (billing for use)
• Electronic consenting systems
• Electronic health record systems (EHRs)
• Laboratory information systems (LIS)
• Radiology Information Systems, PACS (?where was tissue in-
situ?)
• ...

8. Institutional Biobanking
Soares, S. 2012. An integrated informatics approach to institutional biobanking. Master’s thesis

9. Institutional Biobanking Integration “gaps”
• EHR – BIMS interface
• Why  Specimen acquisition through electronic ordering and
existing infrastructure and workflow
• Why  Patient consent (via tethered PHR)
• Why  Phenotype data/annotations for specimen
• OR management system
• Why  OR schedule, acquisition workflow, optimal use of
specimen process resources
• Computerized Order Entry (CPOE)
• Why  facilitate acquisition of serum/saliva/body-fluid
specimens using computerized ordering
• Laboratory Information System
• Why  Leveraging ‘remainder’ samples prior to disposal
Soares, S. 2012. An integrated informatics approach to institutional biobanking. Master’s thesis

10. Lessons from 30 years of data management in healthcare
LESSON #1: System interoperability (integration) is a key to
successful data management in complex and distributed
enterprises
LESSON #2: Standardizing the ‘information model’, data
elements, and coding greatly facilitates information sharing
and distributed data access
What is needed?
a.Develop a common (standard) information model
b.Develop standard meta-data elements (standard attributes)
for entities in the model
c.Develop standards for “encoding” the data with widely
available reference coding systems – work with standards
bodies to add necessary additional codes
• ICD-9 (ICD-10), SNOMED-CT, LOINC

11. Today’s Biobanking
“standards” efforts in the US
• Most ‘standards’ focused on best practices for
operating procedures to create and operate a
biorepository
• Significant emphasis on biospecimen handling,
storage, distribution
• Current work on data management ‘standards’ is
negligible

12. Best Practice Guidelines – NCI, ISBER
http://www.isber.org/bp/documents/ISBERBestPractices3rdedition.pdf http://biospecimens.cancer.gov/bestpractices/2011-NCIBestPractices.pdf

13. Prevailing work on biobanking ‘data standards’
in the US is limited...
• caBIG caTissue model and system
• Design originally focused on specimen collection as part of
clinical trials
• Has been improved but functionality scope limited to specimen
storage/distribution/some clinical data. No accounting, no
collection process. No integration with EHRs. No electronic
consenting or integration with consenting system
• caBIG Common Biospecimen Model (CBM)
• An XML schema and software components to extract data from
site ‘repository management systems’ and submit to NCI for
inclusion in the Specimen Resource Locator repository
• NCI Specimen Resource Locator
• A web-application that allows one to search data exported
voluntarily by biorepositories across the US

14. What is NCI caHUB?
• Part of the NCI’s Biorepositories and Biospecimen
Research Branch (BBRB)
• “caHUB will serve as a reliable source of policies, data,
and standards enabling collection of ....biospecimens
across the research community”
• Mention of a ‘comprehensive informatics
infrastructure’ but not much has transpired
• References caBIG’s Common Biospecimen Model
(last version was 2010, caBIG was de-funded in 2010)

15. Cooperative Human Tissue Network (CHTN)
http://www.chtn.nci.nih.gov/
Upenn, Vanderbilt, Ohio State, Univ. of Virginia, Univ. of Alabama Birmigham, Nationwide Children’s Hospital

16. NCI BBRB’s Minimal Clinical Data Set
http://biospecimens.cancer.gov/bestpractices/Appendix1.pdf

17. News Alert!!!
THIS IS INSUFFICIENT...

18. Standards to Support Federated
and Interoperable Biobanking Information Systems
• Standard biospecimen information model
• Standardized data elements for specimen,
phenotypes, and processing
• “Value sets” from existing coding systems for
encoding the data elements (ie, SNOMED, LOINC,
etc..) – avoids ‘mapping’ to/from various ‘data
dictionaries’
• Data exchange data format and content standards for
specimen information *exchange*
• Data exchange data format and content standards for
specimen use consent (HL-7 CDA for Consent?)

19. European BBMRI
• Originally funded funding from European Commission
(EC) 2007-2011
• European-wide project involving over 50 members and
280 biobanks from over 30 countries
• Goal – distributed research infrastructure using data
and informatics standards to interoperate across the
biobanks
• Spawned several BBMRI country-level efforts
• Dec 2012 -- 14 countries had signed MOU to become
members of the BBMRI European Research
Infrastructure Consortium (BBMRI-EPIC)
• Austria, Bulgaria, Czech Republic, Estonia, Finland, France,
Greece, Italy, Latvia, Malta, Netherlands, Norway, Spain, and
Sweden

20. BBMRI Architecture for Federated Biobanks

21. BBMRI Metadata Model - 2011

22. Consensus across BBMRI-EPIC Countries

23. BBMRI.se – Sweden
http://www.bbmri.se/sv/Om-Oss/

24. BBMRI.se Minimum Information About
Biobank data Sharing (MIABIS)
http://bbmri-wiki.wikidot.com/en:dataset

25. MIABIS Data Elements for Collections
http://bbmri-wiki.wikidot.com/en:dataset-study

26. Biobanks and Cancer Registry Integration
http://bbmri-wiki.wikidot.com/en:eurocourse
MIABIS and Eurocourse Minimum Data Set for Registry Data Sharing

27. Swedish Biobank Registry

28. Europe’s RD Connect and Biobanks

29. RD-Connect Primary Objectives
http://rd-connect.eu/about/objectives/

30. Europe’s BioShare.eu
https://www.bioshare.eu/
12 milliion euros
Dec 2010-Dec 2015
16 Universities and research
institututes
Europe and Canada
9 large biobanks
12 milliion euros
Dec 2010-Dec 2015
16 Universities and research
institututes
Europe and Canada
9 large biobanks
“Development and integration
of data and computing
infrastructures to enable
pooling of data for
investigation of complex
diseases”
“Development and integration
of data and computing
infrastructures to enable
pooling of data for
investigation of complex
diseases”

31. BioShare.eu Activity
• Integration of a number of software applications to
create a ‘stack’ to support distributed biobanking
systems networks
• Data Models
• Phenotype Object Model
• Uses BBMRI-EPIC Minimum Data Set and data model
• Open-source “Mica” platform with integrated software
tools for consortia and biobanks
• Policy documents for datasharing and harmonization

32. BioShare Mission
“BioSHaRE is a consortium of leading biobanks and
international researchres from all domains of biobanking
science. The overall aim of the project is to build upon tools
and methods to achieve solutions for researchers to use
pooled data from different cohort and biobank studies....
This aim will be achieved through the development of
harmonization and standardization...

33. OBIBA – Open Source Software for Biobanks
http://www.obiba.org/

34. Open Source – it really is available...
https://the-ark.atlassian.net/source/browse/ARK/trunk

35. In Conclusion
• US biobaking standards efforts today are largely
ignoring data exchange, interoperability and core
informatics principles to support these activities
• Europe is pushing aggressively ahead on informatics
standards and infrastructure to support federated
biobanking networks
• Neither has considered the standards needed for tight
coupling of biobanks and electronic health record
systems (EHRs), clinical data repositories (CDRs), or
disease registries

36. Questions...