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Towards quantitative read across: Prediction of Ames mutagenicity in a large database.

Authors
  • Benigni, Romualdo1
  • 1 Alpha-Pretox, Via Giovanni Pascoli 1, 00184, Rome, Italy. Electronic address: [email protected] , (Italy)
Type
Published Article
Journal
Regulatory toxicology and pharmacology : RTP
Publication Date
Jul 30, 2019
Volume
108
Pages
104434–104434
Identifiers
DOI: 10.1016/j.yrtph.2019.104434
PMID: 31374229
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

In silico chemical safety assessment can support the evaluation of hazard and risk following potential exposure to a substance, thus stimulating an increased interest for the use of Structure-Activity based approaches by regulatory authorities, particularly QSAR and Read Across. Whereas the longer history of QSAR led to recognize the crucial requirements for predictivity, there are still challenges faced by adopting Read Across to a larger extent in a regulatory setting, namely standardization and objective criteria. In previous research, suitable conditions for applying Read Across to the prediction of the Ames mutagenicity of metabolites and degradation products of pesticides were established: a standardized similarity criterion based simultaneously on basic molecular properties and Structural Similarity was successfully applied to a number of case studies. Here the investigation is extended to a large database of curated Ames mutagenicity results. For around 2,000 chemicals for which the similarity criterion was applicable, the predictivity of Read Across was high: specificity 0.72, sensitivity 0.90, accuracy 0.85. This compares favourably with the Ames test intra-assay variability, and with the predictivity of QSAR models. The need for standardization and rigorous validation of Read Across is emphasized. Copyright © 2019 Elsevier Inc. All rights reserved.

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