Toxicogenomics: a 2020 vision

Zhichao Liu, Ruili Huang, Ruth Roberts, Weida Tong

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)
202 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)92-103
Number of pages12
JournalTrends in Pharmacological Sciences
Volume40
Issue number2
Early online date26 Dec 2018
DOIs
Publication statusPublished - 1 Feb 2019

Keywords

  • Toxicogenomics
  • reproducibility
  • adverse outcome pathways
  • regulatory sciences
  • deep learning
  • toxicogenomics

ASJC Scopus subject areas

  • Toxicology
  • Pharmacology

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