Neural network based models for prediction of LogBB have been reported that have higher accuracy than regression based methods . However, the models produced by regression are considerably faster and hence may be preferred for tasks such as incorporation into the fitness function of a genetic algorithm which require evaluation for a very large number of candidate molecules. In view of these considerations, a PLS regression based model for prediction of LogBB was used in STgrow4 to target GABA-T for the design of potential epileptic drugs.