Quality Assurance in Biobanking for Pre-Clinical Research
Author(s) -
Daniel SimeonDubach,
Steffen M. Zeisberger,
Simon P. Hoerstrup
Publication year - 2016
Publication title -
transfusion medicine and hemotherapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.971
H-Index - 39
eISSN - 1660-3818
pISSN - 1660-3796
DOI - 10.1159/000448254
Subject(s) - biobank , quality assurance , context (archaeology) , translational research , quality (philosophy) , medicine , clinical research , standardization , clinical trial , business , medical physics , operations management , computer science , engineering , bioinformatics , marketing , service (business) , pathology , paleontology , philosophy , epistemology , biology , operating system
It is estimated that not less than USD 28 billion are spent each year in the USA alone on irreproducible pre-clinical research, which is not only a fundamental loss of investment and resources but also a strong inhibitor of efficiency for upstream processes regarding the translation towards clinical applications and therapies. The issues and cost of irreproducibility has mainly been published on pre-clinical research. In contrast to pre-clinical research, test material is often being transferred into humans in clinical research. To protect treated human subjects and guarantee a defined quality standard in the field of clinical research, the manufacturing and processing infrastructures have to strictly follow and adhere to certain (inter-)national quality standards. It is assumed and suggested by the authors that by an implementation of certain quality standards within the area of pre-clinical research, billions of USD might be saved and the translation phase of promising pre-clinical results towards clinical applications may substantially be improved. In this review, we discuss how an implementation of a quality assurance (QA) management system might positively improve sample quality and sustainability within pre-clinically focused biobank infrastructures. Biobanks are frequently positioned at the very beginning of the biomedical research value chain, and, since almost every research material has been stored in a biobank during the investigated life cycle, biobanking seems to be of substantial importance from this perspective. The role model of a QA-regulated biobank structure can be found in biobanks within the context of clinical research organizations such as in regenerative medicine clusters.
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