Trend Analysis of a Database of Intravenous Pharmacokinetic Parameters in Humans for 670 Drug Compounds

TLDR

The study compiles and performs a trend analysis of intravenous pharmacokinetic data for 670 drugs, creating the largest publicly available human PK database. The authors extracted clearance, volume of distribution, mean residence time, and half‑life from IV studies, supplemented with plasma protein binding data, and analyzed these parameters alongside physicochemical descriptors to identify trends. The resulting database confirms known relationships between physicochemical properties and pharmacokinetics, providing a robust resource that supports in silico modeling, scaling, and physiologically based pharmacokinetic development.

Abstract

We present herein a compilation and trend analysis of human i.v. pharmacokinetic data on 670 drugs representing, to our knowledge, the largest publicly available set of human clinical pharmacokinetic data. This data set provides the drug metabolism scientist with a robust and accurate resource suitable for a number of applications, including in silico modeling, in vitro-in vivo scaling, and physiologically based pharmacokinetic approaches. Clearance, volume of distribution at steady state, mean residence time, and terminal phase half-life were obtained or derived from original references exclusively from studies utilizing i.v. administration. Plasma protein binding data were collected from other sources to supplement these pharmacokinetic data. These parameters were analyzed concurrently with a range of simple physicochemical descriptors, and resultant trends and patterns within the data are presented. Our findings with this much expanded data set were consistent with earlier described notions of trends between physicochemical properties and pharmacokinetic behavior. These observations and analyses, along with the large database of human pharmacokinetic data, should enable future efforts aimed toward developing quantitative structure-pharmacokinetic relationships and improving our understanding of the relationship between fundamental chemical characteristics and drug disposition.