Evaluation of QSAR models for predicting the partition coefficient (log P) of chemicals under the REACH regulation

The partition coefficient (log P) is a physicochemical parameter widely used in environmental and health sciences and is important in REACH and CLP regulations. In this regulatory context, the number of existing experimental data on log P is negligible compared to the number of chemicals for which it is necessary. There are many models to predict log P and we have selected a number of free programs to examine how they predict the log P of chemicals registered for REACH and to evaluate wheter they can be used in place of experimental data. Some results are good, especially if the information on the applicability domain of the models is considered, with R2 values from 0.7 to 0.8 and root mean square error (RMSE) from 0.8 to 1.5.