Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
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Training set | training | 114 | 0.791 | 0.714 |
Test set | external validation | 30 | 0.774 | 0.789 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 117 | 0.790 | 0.708 |
Test set | external validation | 32 | 0.773 | 0.767 |
Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 42 | 0.743 | 0.534 |
Test set | external validation | 24 | 0.861 | 0.456 |
Regression model (regression) QMRF
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 46 | 0.743 | 0.559 |
Test set | external validation | 25 | 0.863 | 0.445 |
When using this QDB archive, please cite (see details) it together with the original article:
Piir, G. Data for: Development and validation of a quantitative structure-activity relationship for chronic narcosis to fish. QsarDB repository, QDB.218. 2020. https://doi.org/10.15152/QDB.218
Claeys, L.; Iaccino, F.; Janssen, C. R.; Van Sprang, P.; Verdonck, F. Development and validation of a quantitative structure-activity relationship for chronic narcosis to fish. Environ. Toxicol. Chem. 2013, 32, 2217–2225. https://doi.org/10.1002/etc.2301
Title: | Claeys, L.; Iaccino, F.; Janssen, C. R.; Van Sprang, P.; Verdonck, F. Development and validation of a quantitative structure-activity relationship for chronic narcosis to fish. Environ. Toxicol. Chem. 2013, 32, 2217–2225. |
Abstract: | Abstract Vertebrate testing under the European Union's regulation on Registration, Evaluation, Authorisation and Restriction of Chemical substances (REACH) is discouraged, and the use of alternative nontesting approaches such as quantitative structure?activity relationships (QSARs) is encouraged. However, robust QSARs predicting chronic ecotoxicity of organic compounds to fish are not available. The Ecological Structure Activity Relationships (ECOSAR) Class Program is a computerized predictive system that estimates the acute and chronic toxicity of organic compounds for several chemical classes based on their log octanol?water partition coefficient (KOW). For those chemical classes for which chronic training data sets are lacking, acute to chronic ratios are used to predict chronic toxicity to aquatic organisms. Although ECOSAR reaches a high score against the Organisation for Economic Co-operation and Development (OECD) principles for QSAR validation, the chronic QSARs in ECOSAR are not fully compliant with OECD criteria in the framework of REACH or CLP (classification, labeling, and packaging) regulation. The objective of the present study was to develop a chronic ecotoxicity QSAR for fish for compounds acting via nonpolar and polar narcosis. These QSARs were built using a database of quality screened toxicity values, considering only chronic exposure durations and relevant end points. After statistical multivariate diagnostic analysis, literature-based, mechanistically relevant descriptors were selected to develop a multivariate regression model. Finally, these QSARs were tested for their acceptance for regulatory purposes and were found to be compliant with the OECD principles for the validation of a QSAR. |
URI: | http://hdl.handle.net/10967/218
http://dx.doi.org/10.15152/QDB.218 |
Date: | 2020-03-06 |
Name | Description | Format | Size | View |
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2013ETC2217.qdb.zip | Models for chronic fish toxicity | application/zip | 52.82Kb | View/ |
Q15-35-0006.pdf | QMRF | 36.19Kb | View/ |
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Q15-35-0007.pdf | QMRF | 35.66Kb | View/ |