IT infrastructure components for biobanking
Objective: Within translational research projects in the recent years large biobanks have been established, mostly supported by homegrown, proprietary software solutions. No general requirements for biobanking IT infrastructures have been published yet. This paper presents an exemplary biobanking IT...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2010
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| In: |
Applied clinical informatics
Year: 2010, Jahrgang: 1, Heft: 4, Pages: 419-429 |
| ISSN: | 1869-0327 |
| DOI: | 10.4338/ACI-2010-05-RA-0034 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.4338/ACI-2010-05-RA-0034 Verlag, Volltext: http://www.thieme-connect.de/DOI/DOI?10.4338/ACI-2010-05-RA-0034 
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| Verfasserangaben: | H.U. Prokosch, A. Beck, T. Ganslandt, M. Hummel, M. Kiehntopf, U. Sax, F. Ückert, S. Semler |
MARC
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| 520 | |a Objective: Within translational research projects in the recent years large biobanks have been established, mostly supported by homegrown, proprietary software solutions. No general requirements for biobanking IT infrastructures have been published yet. This paper presents an exemplary biobanking IT architecture, a requirements specification for a biorepository management tool and exemplary illustrations of three major types of requirements. Methods: We have pursued a comprehensive literature review for biobanking IT solutions and established an interdisciplinary expert panel for creating the requirements specification. The exemplary illustrations were derived from a requirements analysis within two university hospitals. Results: The requirements specification comprises a catalog with more than 130 detailed requirements grouped into 3 major categories and 20 subcategories. Special attention is given to multitenancy capabilities in order to support the project-specific definition of varying research and bio-banking contexts, the definition of workflows to track sample processing, sample transportation and sample storage and the automated integration of preanalytic handling and storage robots. Conclusion: IT support for biobanking projects can be based on a federated architectural framework comprising primary data sources for clinical annotations, a pseudonymization service, a clinical data warehouse with a flexible and user-friendly query interface and a biorepository management system. Flexibility and scalability of all such components are vital since large medical facilities such as university hospitals will have to support biobanking for varying monocentric and multicentric research scenarios and multiple medical clients. | ||
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