Modeling Chronic Toxicity: A Comparison of Experimental Variability With (Q)SAR/Read-Across Predictions
This study compares the accuracy of (Q)SAR/read-across predictions with the experimental variability of chronic lowest-observed-adverse-effect levels (LOAELs) from in vivo experiments. We could demonstrate that predictions of the lazy structure-activity relationships (lazar) algorithm within the app...
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| Main Authors: | , , , , , , , |
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| Format: | Book |
| Published: |
Frontiers Media S.A.,
2018-04-01T00:00:00Z.
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| Subjects: | |
| Online Access: | Connect to this object online. |
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| Summary: | This study compares the accuracy of (Q)SAR/read-across predictions with the experimental variability of chronic lowest-observed-adverse-effect levels (LOAELs) from in vivo experiments. We could demonstrate that predictions of the lazy structure-activity relationships (lazar) algorithm within the applicability domain of the training data have the same variability as the experimental training data. Predictions with a lower similarity threshold (i.e., a larger distance from the applicability domain) are also significantly better than random guessing, but the errors to be expected are higher and a manual inspection of prediction results is highly recommended. |
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| Item Description: | 1663-9812 10.3389/fphar.2018.00413 |