Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.
Bibliographical noteFunding Information:
TWG was supported by the National Institutes of Health Research under the Environmental Exposures and Health Protection Research Unit co-led from Imperial College London and Public Health England ( https://eeh.hpru.nihr.ac.uk/ ). ML was supported by the Dutch Ministry of Health , Welfare and Support. This work was supported in part by a European Chemicals Agency contract to Michabo Health Science (ECHA/2018/135) and by the European Chemical Industry Council (Cefic; awarded to BASF , Imperial College London , Syngenta , University of Birmingham and Vrije Universiteit Amsterdam ).
- Metabolomics reporting framework
- Transcriptomics reporting framework
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