Title :
Pharmacokinetic modeling of simvastatin, nelfinavir and their interaction in humans
Author :
Methaneethorn, Janthima ; Kunyamee, Patcharaporn ; Jindasri, Warangkana ; Wattanasaovaluk, Warunee ; Kraiboot, Anoot ; Lohitnavy, Manupat
Author_Institution :
Pharmacokinetic Res. Unit, Naresuan Univ., Phitsanulok, Thailand
Abstract :
Background: Simvastatin, a commonly used HMG-CoA reductase inhibitor, is extensively metabolized by CYP3A4. Therefore, co-administration of simvastatin and CYP3A4 inhibitor can affect simvastatin pharmacokinetics. Nelfinavir, a protease inhibitor, and its major metabolite (M8) are known to be potent CYP3A4 inhibitors. When simvastatin and nelfinavir are co-administered, simvastatin pharmacokinetics is significantly altered and may result in an increased risk of rhabdomyolysis. Objective: To develop a mathematical model describing a drug-drug interaction between simvastatin and nelfinavir in humans. Methods: Eligible pharmacokinetic studies were selected from Pubmed database and concentration time course data were digitally extracted and used for model development. Compartmental pharmacokinetic models for simvastatin and nelfinavir were developed separately. A drug-drug interaction model of simvastatin and nelfinavir was subsequently developed using the prior information. Finally, the final drug-drug interaction modeled was validated against observed simvastatin concentrations. Results: Three compartmental pharmacokinetic models were successfully developed. Simvastatin pharmacokinetics was best described by a one compartment model for simvastatin linked to its active form, simvastatin hydroxy acid. Nelfinavir pharmacokinetics could be adequately described by a one compartment parent-metabolite model. Our final drug-drug interaction model predicted an increase in simvastatin exposure which is in line with clinical observations linking the simvastatin-nelfinavir combination to an increased risk of rhabdomyolysis. Conclusion: Simvastatin-nelfinavir pharmacokinetic interaction can be explained by our final model. This model framework will be useful in further advanced developing other mechanism based drug-drug interaction model used to predict the risk of rhabdomyolysis occurrence in patients prescribed simvastatin and nelfinavir concurrently.
Keywords :
biochemistry; data mining; drug delivery systems; drugs; enzymes; mathematical analysis; medical computing; molecular biophysics; risk analysis; HMG-CoA reductase inhibitor; M8 metabolite; Pubmed database; clinical observations; compartmental pharmacokinetic models; concentration time course data; digital data extraction; drug coadministration effect; drug-drug interaction model validation; human pharmacokinetic modeling; mathematical model; mechanism based drug-drug interaction model; metabolization; nelfinavir pharmacokinetics; nelfinavir prescription; one compartment model; one compartment parent-metabolite model; pharmacokinetic study selection; potent CYP3A4 inhibitor; protease inhibitor; rhabdomyolysis risk prediction; simvastatin active form; simvastatin concentration observation; simvastatin exposure; simvastatin hydroxy acid; simvastatin pharmacokinetics; simvastatin prescription; simvastatin-nelfinavir combination; simvastatin-nelfinavir interaction; simvastatin-nelfinavir pharmacokinetic interaction; Biochemistry; Biological system modeling; Computational modeling; Drugs; Human immunodeficiency virus; Inhibitors; Predictive models;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
DOI :
10.1109/EMBC.2014.6944925