An Integrative Approach for Identifying a Metabolic Phenotype Predictive of Individualized Pharmacokinetics of Tacrolimus

Abstract

Individual variation in drug response is influenced by both genes and environment. We evaluated the potential of a metabolic phenotype to predict individual variation in the pharmacokinetics (PK) of tacrolimus. Liquid chromatography-mass spectroscopy (LC-MS)-based metabolic profiling was performed on 29 healthy volunteers by measuring the levels of 1,256 metabolite ions in their predose urine samples. After oral administration of tacrolimus, we monitored its plasma concentrations in these volunteers for up to 72 h and calculated the pharmacokinetic parameters. Partial least-squares (PLS) modeling was conducted with data relating to predose urine metabolites to predict the pharmacokinetic parameters of tacrolimus and to select the metabolites that substantially contributed to such prediction. The selection of these metabolites allowed us to understand their functional role and generate a clinically applicable index to predict individualized PK of tacrolimus. In conclusion, this integrative pharmacometabolomic approach, combining the metabolic profiling of predose urine with PLS modeling, can serve as a useful tool in "individualized drug therapy.