According to the European REACH Directive, the acute daphnid toxicity needs to be assessed for industrial chemicals with market volumes ≥1 t/a. Employing a data set of 1365 organic compounds with experimental 48-h LC50 data for Daphnia magna, a read-across approach has been developed that makes use of the atom-centered fragment (ACF) method as quantitative measure for structural similarity. Both quantitative log LC50 predictions and a discrimination between narcosis-level and excess toxicity can be obtained, augmented by similarity-triggered information that characterizes a compound as inside or outside the quantitative or qualitative model domain. Reading across proceeds as interpolation of the toxicity enhancement (Te ) over predicted narcosis-level toxicity, taking experimental log Te values from similarity-selected reference compounds as input. The resultant decision tree model yields r(2) =0.85 and rms=0.66 for the subset of 757 compounds (56 %) identified as inside the quantitative model domain, and can handle further 318 compounds (23 %) with the categorical submodel, with 290 compounds (21 %) being outside its domain. The new in silico approach appears useful as ITS (Integrated Testing Strategy) tool for the daphnid toxicity assessment. The discussion includes a comparison of Kow - and LSER-predicted narcosis-level toxicity in the read-across context.
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Kühne et al. (2013) studied this question.
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