Review of (Quantitative) Structure–Activity Relationships for Acute Aquatic Toxicity

Abstract

This paper reviews different approaches described in the literature for estimating the aquatic toxicity of chemical substances. It is based on an extended review performed by the European Chemicals Bureau of the European Commissions Joint Research Centre in support of the development of technical guidance for the implementation of the REACH legislation, and is one of a series of minireviews in this journal. The paper is organised by approach for (Q)SAR development and includes a review of: (i) (Q)SARs for acute aquatic toxicity by chemical class, (ii) (Q)SARs for acute aquatic toxicity by mode of action, (iii) review of statistically derived (Q)SARs, (iv) structural alerts for excess aquatic toxicity and (v) expert systems that combine structural rules and multiple (Q)SAR models to predict aquatic toxicological endpoints. Directions and recommendations for further research are also provided.

Acute toxicity of poly‐ and perfluorinated compounds to two cladocerans, Daphnia magna and Chydorus sphaericus

“…Because the experimental determination of toxicity is costly and time-consuming, predictive models need to be developed to theoretically quantify toxicity. This can be realized by using quantitative structure-activity relationships, which are based on the statistical relationship between the molecular structure of the compound and the corresponding biological activities [21][22][23][24][25].…”

Are the Chemical Structures in Your QSAR Correct?

“…Thus, there has been a great deal of research undertaken in recent years to develop techniques to predict toxicological values without the use of animals. Some of these techniques are semi-empirical, such as (quantitative) structure -activity relationships (Q)SARs [3,4], decision trees [5 -7], and techniques described by Dudek et al [8]. There are other techniques that are based on biological processes, such as those developed to model the dose -response relationship including bioinformatics, chemoinformatics, and molecular modeling [9].…”

Guidance on Grouping of Chemicals, Second Edition

“…(Schultz et al, 2005). Different types of models could be used within a specific mechanistic domain (Netzeva et al, 2008). For substances within the same reactive mechanism of action, the potency of protein binding as predictor for e.g.…”