Literature DB >> 31012352

Development of a read-across workflow for skin irritation and corrosion predictions.

A Abe1, T Sezaki1, K Kinoshita1.   

Abstract

We developed a read-across workflow using the OECD QSAR Toolbox for the prediction of skin irritation and corrosion. In the workflow, we gathered analogues using an improved profiler for skin irritation and corrosion to define valid categories. In addition, we refined categories by removing chemicals based on melting points and structural features. Finally, prediction results were obtained using our self-determined rule for read-across. In this rule, we decided the number of analogues from which the read-across is performed, analogue selection criteria (i.e. high similarity vs. near log Pow) and prediction rule (i.e. majority vs. unanimity). We created a program for the optimization of read-across workflows. We applied this program to 313 chemicals in the training set and sought the optimized workflows among >1000 possible choices of profilers and ways of subcategorization and data gap filling. Use of the optimized workflows provided highly accurate, unbiased, user-independent and reproducible read-across predictions. The prediction results obtained from read-across workflows can be used for the selection of in vitro test methods or as part of the weight-of-evidence approaches in the Integrated Approach on Testing and Assessment for skin irritation and corrosion. Moreover, these results can be used for screening purposes and/or preliminary hazard assessment.

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Keywords:  Integrated Approach on Testing and Assessment (IATA); OECD QSAR Toolbox; read-across; skin irritation and corrosion; workflow

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Year:  2019        PMID: 31012352     DOI: 10.1080/1062936X.2019.1595136

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  1 in total

1.  Clustering a Chemical Inventory for Safety Assessment of Fragrance Ingredients: Identifying Read-Across Analogs to Address Data Gaps.

Authors:  Mihir S Date; Devin O'Brien; Danielle J Botelho; Terry W Schultz; Daniel C Liebler; Trevor M Penning; Daniel T Salvito
Journal:  Chem Res Toxicol       Date:  2020-05-06       Impact factor: 3.739

  1 in total

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