Trend Analysis of a Database of Intravenous Pharmacokinetic Parameters in Humans for 1352 Drug Compounds

• Published in: Drug metabolism and disposition Vol. 46; no. 11; pp. 1466 - 1477
• Main Authors: Lombardo, Franco, Berellini, Giuliano, Obach, R. Scott
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.11.2018; American Society for Pharmacology and Experimental Therapeutics, Inc
• Subjects: Administration, Intravenous; Blood Proteins - metabolism; Data analysis; Data processing; Databases, Factual; Datasets; Drug metabolism; Excretion; Humans; Inactivation, Metabolic - physiology; Intravenous administration; Metabolic Clearance Rate - physiology; Metabolism; Organic chemistry; Parameters; Pharmaceutical Preparations - administration & dosage; Pharmaceutical Preparations - metabolism; Pharmacokinetics; Pharmacology; Physicochemical properties; Properties (attributes); Proteins; Scaling; Tissue Distribution - physiology; Trend analysis; Trends; t1/2; HBA; CL; MW; HBD; MRT; VD; fu; NRB; PSA
• ISSN: 0090-9556; 1521-009X; 1521-009X
• DOI: 10.1124/dmd.118.082966

We report a trend analysis of human intravenous pharmacokinetic data on a data set of 1352 drugs. The aim in building this data set and its detailed analysis was to provide, as in the previous case published in 2008, an extended, robust, and accurate resource that could be applied by drug metabolism, clinical pharmacology, and medicinal chemistry scientists to a variety of scaling approaches. All in vivo data were obtained or derived from original references, either through the literature or regulatory agency reports, exclusively from studies utilizing intravenous administration. Plasma protein binding data were collected from other available sources to supplement these pharmacokinetic data. These parameters were analyzed concurrently with a range of physicochemical properties, and resultant trends and patterns within the data are presented. In addition, the date of first disclosure of each molecule was reported and the potential “temporal” impact on data trends was analyzed. The findings reported here are consistent with earlier described trends between pharmacokinetic behavior and physicochemical properties. Furthermore, the availability of a large data set of pharmacokinetic data in humans will be important to further pursue analyses of physicochemical properties, trends, and modeling efforts and should propel our deeper understanding (especially in terms of clearance) of the absorption, distribution, metabolism, and excretion behavior of drug compounds.