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Updated: Jul 10, 2026

Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Published on: July 11, 2014
Development of predictive quantitative retention-activity relationship models of HMG-CoA reductase inhibitors by
Shu-Rong Wang1, Yu Chen, Li-Ping Wu
1Department of Pharmacy, the Affiliated Hospital of Luzhou Medical College, Luzhou 646000, PR China.
Abstract:
Biological fluid cell membranes are barriers for the uptake of many kinds of drugs and their metabolites, along with passive transport across membranes and bioaccumulation. Biopartitioning micellar chromatography (BMC) is a mode of micellar liquid chromatography that uses micellar mobile phases of Brij35 under adequate experimental conditions and can be useful to simulate the drug's passive absorption and the transport in biological systems. The use of micellar aqueous solutions of Brij35 as mobile phases in reversed-phase liquid chromatography has proven to be valid to predict the biological activities of barbiturates, benzodiazepines, catecholamines, local anesthetics, non-steriodal anti-inflammatory drugs and tricyclic antidepressants. In this study, the relationships between the capacity factor in BMC and some pharmacokinetic and pharmacodynamic parameters of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors are studied. Predictive quantitative retention-activity relationship (QRAR) models describing some of the biological activities and pharmacokinetic properties of HMG-CoA reductase inhibitors are obtained. The results indicate that QRAR model may be a useful tool during the drug discovery process.
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