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      Analysis of Draize Eye Irritation Testing and its Prediction by Mining Publicly Available 2008–2014 REACH Data

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          Summary

          Public data from ECHA online dossiers on 9,801 substances encompassing 326,749 experimental key studies and additional information on classification and labeling were made computable. Eye irritation hazard, for which the rabbit Draize eye test still represents the reference method, was analyzed. Dossiers contained 9,782 Draize eye studies on 3,420 unique substances, indicating frequent retesting of substances. This allowed assessment of the test’s reproducibility based on all substances tested more than once. There was a 10% chance of a non-irritant evaluation after a prior severe-irritant result according to UN GHS classification criteria. The most reproducible outcomes were the results negative (94% reproducible) and severe eye irritant (73% reproducible).

          To evaluate whether other GHS categorizations predict eye irritation, we built a dataset of 5,629 substances (1,931 “irritant” and 3,698 “non-irritant”). The two best decision trees with up to three other GHS classifications resulted in balanced accuracies of 68% and 73%, i.e., in the rank order of the Draize rabbit eye test itself, but both use inhalation toxicity data (“May cause respiratory irritation”), which is not typically available.

          Next, a dataset of 929 substances with at least one Draize study was mapped to PubChem to compute chemical similarity using 2D conformational fingerprints and Tanimoto similarity. Using a minimum similarity of 0.7 and simple classification by the closest chemical neighbor resulted in balanced accuracy from 73% over 737 substances to 100% at a threshold of 0.975 over 41 substances. This represents a strong support of read-across and (Q)SAR approaches in this area.

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          The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics

          The Chemistry Development Kit (CDK) is a freely available open-source Java library for Structural Chemo-and Bioinformatics. Its architecture and capabilities as well as the development as an open-source project by a team of international collaborators from academic and industrial institutions is described. The CDK provides methods for many common tasks in molecular informatics, including 2D and 3D rendering of chemical structures, I/O routines, SMILES parsing and generation, ring searches, isomorphism checking, structure diagram generation, etc. Application scenarios as well as access information for interested users and potential contributors are given.
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            Gephi: An Open Source Software for Exploring and Manipulating Networks

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              Chemical regulators have overreached.

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                Author and article information

                Journal
                100953980
                21906
                ALTEX
                ALTEX
                ALTEX
                1868-596X
                8 April 2017
                11 February 2016
                2016
                07 June 2017
                : 33
                : 2
                : 123-134
                Affiliations
                [1 ]Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Environmental Health Sciences, Baltimore, MD, USA
                [2 ]The Rutgers Center for Computational & Integrative Biology, Rutgers University at Camden, NJ, USA
                [3 ]Department of Chemistry, Rutgers University at Camden, NJ, USA
                [4 ]CAAT-Europe, University of Konstanz, Konstanz, Germany
                Author notes
                Correspondence to: Thomas Hartung, MD PhD Center for Alternatives to Animal Testing Johns Hopkins Bloomberg School of Public Health 615 N. Wolfe Str., Baltimore, MD, 21205, USA, thartun1@ 123456jhu.edu
                Article
                NIHMS858848
                10.14573/altex.1510053
                5461467
                26863293
                3fbe82c6-403e-4be9-ad55-9936d6a227d9

                This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International license ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is appropriately cited.

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                animal testing alternatives,ocular toxicity,in silico,dataset,chemical safety

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