Predicting Lipophilicity of Drug-Discovery Molecules using Gaussian Process Models

The lipophilicity of 14 556 library compounds at Bayer Schering was modeled using Gaussian process methodology. In a blind test with 7013 new drug‐discovery molecules from the last few months, 81 % were predicted correctly within one log unit, compared with only 44 % achieved by commercial software. Predicted error bars exhibit close to ideal statistical properties, thereby allowing assessment of the model's domain of applicability.