QSARS for the eye irritation potential of neutral organic chemicals

Abstract

A quantitative structure-activity relationship (QSAR) was derived previously relating European Community (EC) eye irritation classification data of a set of neutral organic chemicals, to log(octanol/water partition coefficient), to the minor principal inertial axes (Ry and Rz) and to dipole moment. Eye irritation scores on a scale of 1–10 for a set of aliphatic alcohols (from the work of Smyth and Carpenter) have been shown to correlate well with the same four physicochemical parameters by means of neural network analysis. The original classification dataset of neutral organic chemicals has been augmented by the addition of a number of the aliphatic alcohols from the Smyth and Carpenter data that could unequivocally be assigned the EC classifications of irritant (those with eye irritation scores of 8 and 9) or non-irritant (scores of 1). Analysis of the extended dataset by both principal components and neural network analysis showed a clear discrimination between irritant and non-irritant chemicals using the same four physicochemical parameters. Predictions of EC eye irritation classifications for aliphatic alcohols with eye scores of 2–7, using the neural network model, showed that alcohols with eye scores of 2 and 3 lie on the classification boundary between irritant and non-irritant whereas those with scores of 4 and above are classified as irritant. These analyses support the validity of the original four-parameter eye irritation QSAR model for neutral organic chemicals. Furthermore, they provide a method for interrelating sets of in vivo data in which the biological response parameters are expressed in quite different formats, providing a means of utilizing historical data and thereby extending the availability of in vivo data suitable for the validation of in vitro alternative methods.