Physiologically Based Modeling of Pravastatin Transporter-Mediated Hepatobiliary Disposition and Drug-Drug Interactions

• Published in: Pharmaceutical research 2012-10, Vol.29 (10), p.2860-2873
• Main Authors: Varma, Manthena V. S., Lai, Yurong, Feng, Bo, Litchfield, John, Goosen, Theunis C., Bergman, Arthur
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Aged; Area Under Curve; Biochemistry; Biological and medical sciences; Biological Transport; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Cells, Cultured; Computer Simulation; Cyclosporine - administration & dosage; Cyclosporine - pharmacokinetics; Drug Interactions; Enzyme Inhibitors - administration & dosage; Enzyme Inhibitors - pharmacokinetics; Female; Gemfibrozil - administration & dosage; Gemfibrozil - pharmacokinetics; General pharmacology; Hepatocytes - metabolism; Humans; Kinetics; Liver - metabolism; Male; Medical Law; Medical sciences; Middle Aged; Organic Anion Transporters - antagonists & inhibitors; Pharmaceutical sciences; Pharmaceutical technology. Pharmaceutical industry; Pharmacology; Pharmacology. Drug treatments; Pharmacology/Toxicology; Pharmacy; Pravastatin - administration & dosage; Pravastatin - pharmacokinetics; Pravastatin - pharmacology; Research Paper; Rifampin - administration & dosage; Rifampin - pharmacokinetics; Solute Carrier Organic Anion Transporter Family Member 1b1; Statins; Young Adult
• ISSN: 0724-8741; 1573-904X
• DOI: 10.1007/s11095-012-0792-7

ABSTRACT Purpose To develop physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and drug-drug interactions (DDI) of pravastatin, using the in vitro transport parameters. Methods In vitro hepatic sinusoidal active uptake, passive diffusion and canalicular efflux intrinsic clearance values were determined using sandwich-culture human hepatocytes (SCHH) model. PBPK modeling and simulations were implemented in Simcyp (Sheffield, UK). DDI with OATP1B1 inhibitors, cyclosporine, gemfibrozil and rifampin, was also simulated using inhibition constant (Ki) values. Results SCHH studies suggested active uptake, passive diffusion and efflux intrinsic clearance values of 1.9, 0.5 and 1.2 μL/min/10 6 cells, respectively, for pravastatin. PBPK model developed, using transport kinetics and scaling factors, adequately described pravastatin oral plasma concentration-time profiles at different doses (within 20% error). Model based prediction of DDIs with gemfibrozil and rifampin was similar to that observed. However, pravastatin-cyclosporine DDI was underpredicted (AUC ratio 4.4 Vs ~10). Static (R-value) model predicted higher magnitude of DDI compared to the AUC ratio predicted by the PBPK modeling. Conclusions PBPK model of pravastatin, based on in vitro transport parameters and scaling factors, was developed. The approach described can be used to predict the pharmacokinetics and DDIs associated with hepatic uptake transporters.