A large database of milk/plasma ratios, M/P, for 179 drugs and hydrophobic environmental pollutants has been constructed from literature data. Application of linear analyses shows that drugs preferentially partition into the aqueous and the protein phases of milk, but that the pollutants partition into the fat phase. No useful linear equation could be obtained for the entire 179 compound data set, but an artificial neural network with only five Abraham descriptors as input resulted in errors in log(1 þ M/P) of only 0.0574, 0.116 and 0.093 log units for a training set of 135 compounds, an internal test set of 22 compounds and an external test set of 22 compounds respectively. These errors correspond to 0.203, 0.193 and 0.334 log units respectively when transformed into errors in log(M/P)
