4.7 Review

Quantitative adverse outcome pathway (qAOP) models for toxicity prediction

期刊

ARCHIVES OF TOXICOLOGY
卷 94, 期 5, 页码 1497-1510

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s00204-020-02774-7

关键词

Predictive toxicology; Quantitative adverse outcome pathway (qAOP); Computational approach; Bayesian network; Response-response relationship; Key event relationship

资金

  1. European Union Marie Sklodowska-Curie Action Innovative Training Network in3 Project, Directorate-General for Research and Innovation [721975]

向作者/读者索取更多资源

The quantitative adverse outcome pathway (qAOP) concept is gaining interest due to its potential regulatory applications in chemical risk assessment. Even though an increasing number of qAOP models are being proposed as computational predictive tools, there is no framework to guide their development and assessment. As such, the objectives of this review were to: (i) analyse the definitions of qAOPs published in the scientific literature, (ii) define a set of common features of existing qAOP models derived from the published definitions, and (iii) identify and assess the existing published qAOP models and associated software tools. As a result, five probabilistic qAOPs and ten mechanistic qAOPs were evaluated against the common features. The review offers an overview of how the qAOP concept has advanced and how it can aid toxicity assessment in the future. Further efforts are required to achieve validation, harmonisation and regulatory acceptance of qAOP models.

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