EXTRAPOLATION OF PRECLINICAL PHARMACOKINETICS AND MOLECULAR FEATURE ANALYSIS OF “DISCOVERY-LIKE ” MOLECULES TO PREDICT HUMAN PHARMACOKINETICS

The prediction of human pharmacokinetics from preclinical spe-cies is an integral component of drug discovery. Recent studies with a 103-compound dataset suggested that scaling frommonkey pharmacokinetic data tended to be the most accurate method for predicting human clearance. Additionally, interrogation of the two-dimensional molecular properties of these molecules produced a set of associations which predict the likely extrapolative outcome (success or failure) of preclinical data to project human pharma-cokinetics. However, a limitation of the previous analyses was the relative paucity of data for typical “discovery-like ” molecules (mo-lecular weight>300 and/or clogP>3). The objective of this inves-tigation was to generate preclinical data required for extension of this dataset for additional discovery-like molecules and determine whether the aforementioned findings continue to apply for these molecules. In vivo nonrodent intravenous pharmacokinetic dat