Serum Predose Metabolic Profiling for Prediction of Rosuvastatin Pharmacokinetic Parameters in Healthy Volunteers - Silveira, Anne Michelli Reis; Duarte, Gustavo Henrique Bueno; Fernandes, Anna Maria Alves de Piloto; Garcia, Pedro Henrique Dias; Vieira, Nelson Rogerio; Antonio, Marcia Aparecida; Carvalho, Patricia de Oliveira (Frontiers in Pharmacology, 2021)
Rosuvastatin is a well known lipid-lowering agent generally used for hypercholesterolemia treatment and coronary artery disease prevention. There is substantial inter-individual variability in the absorption of statins usually caused by genetic polymorphisms leading to variation in the corresponding pharmacokinetics parameters, which may affect drug therapy safety and efficacy. Therefore, the investigation of metabolic markers associated with rosuvastatin inter-individual variability is exceedingly relevant for drug therapy optimization and minimizing side effects. This work describes the application of pharmacometabolomics strategies using liquid chromatography coupled to mass spectrometry to investigate endogenous plasma metabolites capable of predicting pharmacokinetic parameters in predose samples. First, a targeted method for determination of plasma concentration levels of rosuvastatin was validated and applied to obtain the pharmacokinetic parameters from the 40 enrolled individuals, then predose samples were analyzed using a metabolomics approach to search for associations between endogenous metabolites and the corresponding pharmacokinetic parameters. Data processing using machine learning revealed some candidates including sterols and bile acids, carboxylated metabolites and lipids, suggesting the approach herein described as promising for personalized drug therapy.