Abstract
Biobanking is the science and practice of storing biological specimens for future use. Biobanking is an emerging field with the potential to improve our understanding of disease and develop better, more targeted treatments for many conditions. Data associated with the specimens must include information about the specimens, the donor, and the conditions (including informed consent) under which the samples were collected, processed, and stored. Biobanking is based upon the premise that the storage of biologic specimens will enable future research, including the use of advanced technologies and methods beyond what currently exists, and without associated data, samples cannot be leveraged for the future. With the completion of the human genome and the promise of personalized medicine and diagnostics, biobanking is being embraced by a variety of stakeholders, including academic institutions, government, industry, and patient advocacy groups. This wide-ranging adoption has led to the development of many biobanks for various purposes. These different categories of biobanks, from population biobanks to disease-specific biobanks, collect a variety of human specimen types, each requiring different descriptive data and associated standards for collection, processing, and storage. In this chapter, we discuss the challenges inherent in biobanking and opportunities for informatics to resolve some of these challenges.
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References
Park A. 10 ideas changing the world right now. Time. 2009. http://www.time.com/time/specials/packages/article/0,28804,1884779_1884782_1884766,00.html. Accessed 15 Oct 2010.
Hamburg MA, Collins FS. The path to personalized medicine. N Engl J Med. 2010;363:301–4. doi:10.1056/NEJMp1006304.
Troyer D. Biorepository standards and protocols for collecting, processing, and storing human tissues. Methods Mol Biol. 2008;441:193–220. doi:10.1007/978-1-60327-047-2.
Pendergrass S, Dudek SM, Roden DM, Crawford DC, Ritchie MD. Visual integration of results from a large DNA biobank (biovu) using synthesis-view. Pac Symp Biocomput. 2011;265–275. doi:10.1142/9789814335058_0028.
Paik S, Kim CY, Song YK, Kim WS. Technology insight: application of molecular techniques to formalin-fixed paraffin-embedded tissues from breast cancer. Nat Clin Pract Oncol. 2005;2:246–54. doi:10.1038/ncponc0171.
Austin MA, Harding S, McElroy C. Genebanks: a comparison of eight proposed international genetic databases. Community Genet. 2003;6:37–45. doi:10.1159/000069544.
Hawkins AK. Biobanks: importance, implications and opportunities for genetic counselors. J Genet Couns. 2010;19:423–9. doi:10.1007/s10897-010-9305-1.
Terry SF, Terry PF, Rauen KA, Uitto J, Bercovitch LG. Advocacy groups as research organizations: the PXE international example. Nat Rev Genet. 2007;8:157–64. doi:10.1038/nrg1991.
S.F. Terry, E.J. Horn, J. Scott, P.F. Terry. Genetic Alliance Registry and BioBank: a novel disease advocacy-driven research solution. Personalized Medicine, 8(2):207–13, March 2011
Compton CC. The surgical specimen is the personalized part of personalized cancer medicine. Ann Surg Oncol. 2009;16:2079–80. doi:10.1245/s10434-009-0526-1.
Lim MD, Dickherber A, Compton CC. Before you analyze a human specimen, think quality, variability, and bias. Anal Chem. 2011;83:8–13. doi:10.1021/ac1018974.
Compton CC. Rare disease biospecimens: quality and accessibility challenges. Advancing rare disease research: the intersection of patient registries, biospecimen repositories, and clinical data. 2010. http://rarediseases.info.nih.gov/PATIENT_REGISTRIES_WORKSHOP/. Accessed 15 Oct 2010.
Beskow LM, Friedman JY, Hardy NC, Lin L, Weinfurt KP. Developing a simplified consent form for biobanking. PLoS One. 2010;5:e13302. doi:10.1371/journal.pone.0013302.
Office of Biorepositories and Biospecimen Research. NCI best practices for biospecimen resources. National Cancer Institute. 2010. http://biospecimens.cancer.gov/bestpractices/. Accessed 15 Oct 2010.
Pitt KE, Cambell LD, Skubitx APN, Somiari SB, Sexton KC, Pugh RS. Best practices for repositories: collection, storage, retrieval and distribution of biological materials for research. Cell Preserv Technol. 2008;6:5–58. doi:10.1089/cpt.2008.9997.
Office of Biorepositories and Biospecimen Research. caHUB: the cancer human biobank. National Cancer Institute. 2010. http://cahub.cancer.gov/. Accessed 15 Oct 2010.
National Cancer Institute. caBIG: cancer Biomedical Informatics Grid. 2010. http://cabig.Âcancer.gov/. Accessed 10 Dec 2010.
BBMRI: Biobanking and Biomolecular Resources Research Infrastructure. Managing resources for the future of biomedical research. 2010. http://www.bbmri.eu/. Accessed 15 Oct 2010.
International Society for Biological and Environmental Repositories. ISBER self-assessment tool (SAT). 2009. https://secure.asip.org/CVWEB_ISBER/Library/sat.htm. Accessed Aug 2011.
Kelly A. Biospecimen reporting for improved study quality: BRISQ. caBIG: cancer Biomedical Informatics Grid. 2010. https://cabig.nci.nih.gov/workspaces/TBPT/Meetings/TBPT_Workspace/19July10_TBPT. Accessed 15 Oct 2010.
Betsou F, Lehmann S, Ashton G. Standard preanalytical coding for biospecimens: defining the sample PREanalytical code. Cancer Epidemiol Biomarkers Prev. 2010;19:1004–11. doi:10.1158/1055-9965.EPI-09-1268.
SPIDIA Consortium. SPIDIA: standardisation and improvement of generic pre-analytical tools and procedures for in-vitro diagnostics. 2011. http://www.spidia.eu/. Accessed 15 Oct 2010.
Riegman PH, de Jong BW, Llombart-Bosch A. The Organization of European Cancer Institute Pathobiology Working Group and its support of European biobanking infrastructures for translational cancer research. Cancer Epidemiol Biomarkers Prev. 2010;19:923–6. doi:10.1158/1055-9965.EPI-10-0062.
Office of Information Services. National health and nutrition examination survey. Centers for Disease Control and Prevention. 2010. http://www.cdc.gov/nchs/nhanes.htm. Accessed 10 Dec 2010.
National Institute of Health. PROMIS: patient-reported outcomes measurement information system. 2010. http://www.nihpromis.org/default.aspx. Accessed 10 Dec 2010.
RTI International. PhenX: consenus measures for phenotypes and exposures. 2010. https://www.phenx.org. Accessed 10 Dec 2010.
National Center for Biotechnology Information. dbGaP: database of genotypes and phenotypes. 2011. http://www.ncbi.nlm.nih.gov/gap. Accessed 10 Dec 2010.
PRISM: Patient registry item specifications and metadata for rare diseases. http://prism.epi.usf.edu/prism/. Accessed 10 Dec 2010.
HL7: Health Level Seven International. 2011 http://www.hl7.org/. Accessed 10 Dec 2010.
Regenstrief Institute, Inc. LOINC: logical observation identifiers names and codes. 2011. http://loinc.org/. Accessed 10 Dec 2010.
International Health Terminology Standards Development Organisation. SNOMED CT. 2010. http://www.ihtsdo.org/snomed-ct/. Accessed 10 Dec 2010.
U.S. National Library of Medicine. RxNorm. Unified Medical Language System (UMLS). 2010. http://www.nlm.nih.gov/research/umls/rxnorm/. Accessed 10 Dec 2010.
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Horn, E.J., Terry, S.F. (2012). Biobanking Challenges and Informatics Opportunities. In: Richesson, R., Andrews, J. (eds) Clinical Research Informatics. Health Informatics. Springer, London. https://doi.org/10.1007/978-1-84882-448-5_12
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DOI: https://doi.org/10.1007/978-1-84882-448-5_12
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