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Updated: Mar 13, 2026

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management
Published on: November 30, 2022
Quality Assurance in Biobanking for Pre-Clinical Research
Daniel Simeon-Dubach1, Steffen M Zeisberger2, Simon P Hoerstrup3
1Medservice, Biobanking Consulting & Services, Walchwil, Switzerland.
Abstract:
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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