A QSAR model for the eye irritation of cationic surfactants.
A QSAR model for the eye irritation of cationic surfactants has been constructed using a dataset consisting of the maximum average scores (MAS-accordance to Draize) for 29 in vivo rabbit eye irritation tests on 19 different cationic surfactants. The parameters used were logP (log [octanol/water partition coefficient]) and molecular volume (to model the partition of the surfactants into the membranes of the eye), logCMC (log critical micelle concentration-a measure of the reactivity of the surfactants with the eye) together with surfactant concentration. The model was constructed using neural network analysis. MAS showed strongly positive, non-linear correlations with surfactant concentration and logCMC and a strongly negative, non-linear correlation with logP. The Pearson correlation between the actual and predicted values of MAS was 0.838 showing that around 70% (r(2)=0.702) of the variance in the dataset is explained by the model. This value is consistent with levels of biological variability reported historically for the Draize rabbit eye test. The relationship provides a potentially useful prediction model for the eye irritation potential of new or untested cationic surfactants with physicochemical properties lying within the parameter space of the model.
Patlewicz
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SEAC Toxicology Unit, Colworth House, Sharnbrook, Bedford MK44 1LQ, UK.
Rodford
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Ellis
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Barratt
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D000818:Animals; D002412:Cations / Q000633:toxicity; D002463:Cell Membrane Permeability; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D005123:Eye / Q000187:drug effects*; D007509:Irritants / Q000633:toxicity*; D008823:Micelles; D008954:Models, Biological; D008970:Molecular Weight; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010539:Permeability; D011817:Rabbits; D012869:Skin Absorption; D013329:Structure-Activity Relationship; D013501:Surface-Active Agents / Q000633:toxicity*
D002412:Cations; D007509:Irritants; D008823:Micelles; D013501:Surface-Active Agents