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Trends Pharmacol Sci. 2019 Feb;40(2):92-103. doi: 10.1016/j.tips.2018.12.001. Epub 2018 Dec 26.

Toxicogenomics: A 2020 Vision.

Author information

1
National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA. Electronic address: zhichao.liu@fda.hhs.gov.
2
National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20850, USA.
3
ApconiX, BioHub at Alderley Park, Alderley Edge, SK10 4TG, UK; University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
4
National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA. Electronic address: weida.tong@fda.hhs.gov.

Abstract

Toxicogenomics (TGx) has contributed significantly to toxicology and now has great potential to support moves towards animal-free approaches in regulatory decision making. Here, we discuss in vitro TGx systems and their potential impact on risk assessment. We raise awareness of the rapid advancement of genomics technologies, which generates novel genomics features essential for enhanced risk assessment. We specifically emphasize the importance of reproducibility in utilizing TGx in the regulatory setting. We also highlight the role of machine learning (particularly deep learning) in developing TGx-based predictive models. Lastly, we touch on the topics of how TGx approaches could facilitate adverse outcome pathways (AOP) development and enhance read-across strategies to further regulatory application. Finally, we summarize current efforts to develop TGx for risk assessment and set out remaining challenges.

KEYWORDS:

adverse outcome pathways; deep learning; regulatory sciences; reproducibility; toxicogenomics

PMID:
30594306
DOI:
10.1016/j.tips.2018.12.001
[Indexed for MEDLINE]
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