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Framework for the quality assurance of ’omics technologies considering GLP requirements
Citation:
Kauffmann, H., R. Fuchs, B. Chorley, L. Deferme, J. Hackermüller, S. Perdichizzi, A. Poole, U. Sauer, K. Tollefsen, T. Tralau, C. Yauk, B. van Ravenzwaay, H. Kamp, AND T. Ebbels. Framework for the quality assurance of ’omics technologies considering GLP requirements. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, 12(91):s27-s35, (2017). https://doi.org/10.1016/j.yrtph.2017.10.007
Impact/Purpose:
In order to use the data obtained in ‘omics-based studies for regulatory purposes, it would be beneficial (and in some cases, it would be indispensable) to also conduct these investigations according to the principles of Good Laboratory Practices (GLP).To date, guidance is unavailable on how to conduct ‘omics studies under GLP (or GLP-like) conditions. In addressing this deficiency, the establishment of a GLP(-like) context for collecting, storing and curating ‘omics data was one of the key objectives of the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) workshop Applying ‘omics technologies in chemical risk assessment, that took place on 10-12 October 2016 in Madrid, Spain. The article summarizes the discussion and ideas that were generated on this topic at the ECETOC workshop.
Description:
‘Omics technologies are gaining importance to support regulatory toxicity studies. Prerequisites for performing ‘omics studies considering GLP principles were discussed at the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) Workshop Applying ‘omics technologies in Chemical Risk Assessment. A GLP environment comprises a standard operating procedure system, proper pre-planning and documentation, and inspections of independent quality assurance staff. To prevent uncontrolled data changes, the raw data obtained in the respective ‘omics data recording systems have to be specifically defined. Further requirements include transparent and reproducible data processing steps, and safe data storage and archiving procedures. The software for data recording and processing should be validated, and data changes should be traceable or disabled. GLP-compliant quality assurance of ‘omics technologies appears feasible for many GLP requirements. However, challenges include (i) defining, storing, and archiving the raw data; (ii) transparent descriptions of data processing steps; (iii) software validation; and (iv) ensuring complete reproducibility of final results with respect to raw data. Nevertheless, ‘omics studies can be supported by quality measures (e.g., GLP principles) to ensure quality control, reproducibility and traceability of experiments. This enables regulators to use ‘omics data in a fit-for-purpose context, which enhances their applicability for risk assessment.
URLs/Downloads:
DOI: Framework for the quality assurance of ’omics technologies considering GLP requirements