The Breneman research group primarily specializes in the development of new molecular property descriptors and machine learning methods that can be applied to a diverse set of physical and biochemical problems. Of paramount interest are methods that can increase the information content of molecular descriptors, and machine learning techniques that can exploit this data for the creation of fully validated, predictive property models. Current application areas include pharmaceutical ADME prediction, virtual high-throughput screening of drug candidates, protein chromatography modeling (HIC and ion-exchange), as well as polymer property prediction.