Austin, T.J.; Eadsforth, C.V. Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. SAR QSAR Environ. Res. 2014, 25, 147–160.

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Austin, T.J.; Eadsforth, C.V. Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. SAR QSAR Environ. Res. 2014, 25, 147–160.

QDB archive DOI: 10.15152/QDB.145   DOWNLOAD

QsarDB content

Property logNOEC: Chronic fish toxicity [log((mmol/L)] i

Tab3_New: Non-polar narcotics

Regression model (regression)   QMRF

Open in:QDB ExplorerQDB Predictor

NameTypen

R2

σ

Training settraining190.9070.374
Validation setexternal validation100.8850.453

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  • Kahn, I. Data for: Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. QsarDB repository, QDB.145. 2015. http://dx.doi.org/10.15152/QDB.145

  • Austin, T. J.; Eadsforth, C. V. Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. SAR QSAR Environ. Res. 2014, 25, 147–160. http://dx.doi.org/10.1080/1062936x.2013.871577

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Title: Austin, T.J.; Eadsforth, C.V. Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics. SAR QSAR Environ. Res. 2014, 25, 147–160.
Abstract:To comply with the REACH (Registration, Evaluation, Authorisation and restriction of Chemicals) regulations, the generation of chronic fish toxicity data is required for chemicals produced or imported within or into the EU in quantities greater than 100 tonnes per year. This comes at a great cost to industry and consumers alike and requires the sacrifice of many vertebrates. In acknowledgment of these issues the REACH regulations encourage the use of non-testing methods (NTM). These include read-across, weight-of-evidence and QSAR (quantitative structure–activity relationship) techniques. There are many QSAR tools available to generate predictive values for a number of physico-chemical properties, as well as human and environmental health end points; however, close analysis of the currently available chronic fish models identified room for improvement in both the selection of data used and in its application in model creation. In light of this a model was developed using only sub-lethal no-observed-effect concentration (NOEC) end-point data according to best practice QSAR development. Only the lowest value was taken for each compound, in line with the conservative approach taken by the European Chemicals Agency (ECHA). The model developed meets the Organisation for Economic Co-operation and Development (OECD) principles, has strong internal and external validation statistics, and can reliably predict sub-lethal chronic NOEC values for fish within its defined applicability domain.
URI:http://hdl.handle.net/10967/145
http://dx.doi.org/10.15152/QDB.145
Date:2015-03-31


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