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Mutat Res. 2019 Nov;847:403022. doi: 10.1016/j.mrgentox.2019.02.003. Epub 2019 Feb 21.

High information content assays for genetic toxicology testing: A report of the International Workshops on Genotoxicity Testing (IWGT).

Author information

1
Litron Laboratories, Rochester, NY, USA. Electronic address: sdertinger@litronlabs.com.
2
Division of Carcinogenesis and Cancer Prevention, National Cancer Center Research Institute, Tokyo, Japan.
3
Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
4
Mechanistic Safety and ADME Sciences, DSM, IMED Biotech Unit, AstraZeneca, Cambridge, UK.
5
Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands.
6
Division of Genetics & Mutagenesis, National Institute of Health Sciences, Kanagawa, Japan.
7
Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada.
8
Pfizer Global Research and Development, Groton, CT, USA.
9
Sanofi, Vitry-sur-Seine, France.
10
Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada. Electronic address: carole.yauk@canada.ca.

Abstract

We live in an era of 'big data', where the volume, velocity, and variety of the data being generated is increasingly influencing the way toxicological sciences are practiced. With this in mind, a workgroup was formed for the 2017 International Workshops on Genotoxicity Testing (IWGT) to consider the use of high information content data in genetic toxicology assessments. Presentations were given on adductomics, global transcriptional profiling, error-reduced single-molecule sequencing, and cellular phenotype-based assays, which were identified as methodologies that are relevant to present-day genetic toxicology assessments. Presenters and workgroup members discussed the state of the science for these methodologies, their potential use in genetic toxicology, current limitations, and the future work necessary to advance their utility and application. The session culminated with audience-assisted SWOT (strength, weakness, opportunities, and threats) analyses. The summary report described herein is structured similarly. A major conclusion of the workgroup is that while conventional regulatory genetic toxicology testing has served the public well over the last several decades, it does not provide the throughput that has become necessary in modern times, and it does not generate the mechanistic information that risk assessments ideally take into consideration. The high information content assay platforms that were discussed in this session, as well as others under development, have the potential to address aspect(s) of these issues and to meet new expectations in the field of genetic toxicology.

KEYWORDS:

Adductomics; Error-reduced sequencing; Genetic toxicology; High information content; New technologies; Transcriptomics

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