How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology

@inproceedings{Wittwehr2017HowAO,
  title={How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology},
  author={Clemens Wittwehr and Hristo T. Aladjov and Gerald T. Ankley and Hugh J. Byrne and Joop de Knecht and Elmar Heinzle and Guenter Klambauer and Brigitte Landesmann and Mirjam Luijten and Cameron Mackay and Gavin Maxwell and M. E. Meek and Alicia Paini and Edward J. Perkins and Tomasz Sobanski and Dan Villeneuve and Katrina M. Waters and Maurice P. Whelan},
  booktitle={Toxicological sciences : an official journal of the Society of Toxicology},
  year={2017}
}
Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems… CONTINUE READING

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Extracting and Benchmarking Emerging Adverse Outcome Pathway Knowledge.

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  • 2019
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References

Publications referenced by this paper.
SHOWING 1-10 OF 72 REFERENCES

Adverse outcome pathways: hype or hope?

VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Consensus approach for modeling HTS assays using in silico descriptors

A. Abdelaziz Sayed, H. Spahn-Langguth, K. Werner-Schramm, I. V. Tetko
  • Front. Environ. Sci. 4, 2.
  • 2016
VIEW 1 EXCERPT