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Transl Respir Med. 2013 Dec;1(1):14. doi: 10.1186/2213-0802-1-14. Epub 2013 Aug 30.

Standardization developments for large scale biobanks in smoking related diseases - a model system for blood sample processing and storage.

Author information

1
Department of Laboratory Medicine, Section for Clinical Chemistry, Lund University, Skåne University Hospital in Malmö, Malmö, 205 02, Sweden.
2
Clinical Protein Science & Imaging, Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, 221 84, Lund, Sweden.
3
Region Skåne R&D Center, Region Skåne, 221 85, Lund, Sweden.
4
Department of Oncology, Clinical Sciences, Lund University, 221 85, Lund, Sweden.
5
Region Skåne Biobank, Skåne University Hospital, 221 85, Lund, Sweden.
6
Thermo Fisher Scientific, Stafford House, 1 Boundary Park, Hemel Hempstead, Hertfordshire, HP2 7GE, UK.
7
Thermo Fisher Scientific, Rochester, MA, 14625, USA.
8
Respiratory and Inflammation Therapy Area, Astra Zeneca R&D, 431 83, Mölndal, Sweden.
9
Department of Cardiology, Lund University, Skåne University Hospital, 221 85, Lund, Sweden.
10
Clinical Protein Science & Imaging, Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, 221 84, Lund, Sweden. gyorgy.marko-varga@elmat.lth.se.
11
First Department of Surgery, Tokyo Medical University, 6-7-1 Nishishinjiku Shinjiku-ku, Tokyo, 160-0023, Japan. gyorgy.marko-varga@elmat.lth.se.

Abstract

BACKGROUND:

Biobank samples stored in biobanks give researchers and respiratory healthcare institutions access to datasets of analytes valuable for both diagnostic and research practices. The usefulness of these samples in clinical decision-making is highly dependent on their quality and integrity. New procedures that better preserve sample integrity and reduce degradation are being developed to meet the needs of both present and future biobanking. Hereby we present an automatic sample workflow scheme that is designed to handle high numbers of blood samples.

METHODS:

Blood fractions are aliquoted, heat sealed using novel technology, and stored in 384 tube high-density sample arrays.

RESULTS:

The newly developed 384 biobank rack system is especially suited for preserving identical small aliquots. We provide data on robotic processing of clinical samples at -80°C, following initial processing, analysis and shipping between laboratories throughout Europe. Subsequent to unpacking, re-sorting, and storage at these sites, the samples have been returned for analysis. Biomarker analysis of 13 common tests in the clinical chemistry unit of the hospital provides evidence of qualitative and stable logistics using the 384-sample tube system.

CONCLUSIONS:

This technology development allows rapid access to a given sample in the frozen archive while maintaining individual sample integrity with sample tube confinement and quality management.

KEYWORDS:

Biobank; Biomarkers; Respiratory diseases; Robotics; Standardization

PMID:
27234395
DOI:
10.1186/2213-0802-1-14

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