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Predicting individual responses to pravastatin using a physiologically based kinetic model for plasma cholesterol concentrations

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Author: Pas, N.C.A. van de · Rullmann, J.A.C. · Woutersen, R.A. · Ommen, B. van · Rietjens, I.M.C.M. · Graaf, A.A. de
Type:article
Date:2014
Source:Journal of Pharmacokinetics and Pharmacodynamics, 4, 41, 351-362
Identifier: 516504
doi: doi:10.1007/s10928-014-9369-x
Keywords: Biology · Cholesterol · LDL · PBK modeling · Personalized medicine · Statin response · Virtual subjects · cholesterol · High density lipoprotein cholesterol · Low density lipoprotein cholesterol · Low density lipoprotein receptor · Pravastatin · Very low density lipoprotein cholesterol · Cholesterol blood level · Cholesterol synthesis · Drug effect · Drug mechanism · Human · Kinetics · Major clinical study · Monte Carlo method · Physiologically based kinetic · Protein expression · Biomedical Innovation · Healthy Living · Life · MSB - Microbiology and Systems Biology · ELSS - Earth, Life and Social Sciences

Abstract

We used a previously developed physiologically based kinetic (PBK) model to analyze the effect of individual variations in metabolism and transport of cholesterol on pravastatin response. The PBK model is based on kinetic expressions for 21 reactions that interconnect eight different body cholesterol pools including plasma HDL and non-HDL cholesterol. A pravastatin pharmacokinetic model was constructed and the simulated hepatic pravastatin concentration was used to modulate the reaction rate constant of hepatic free cholesterol synthesis in the PBK model. The integrated model was then used to predict plasma cholesterol concentrations as a function of pravastatin dose. Predicted versus observed values at 40 mg/d pravastatin were 15 versus 22 % reduction of total plasma cholesterol, and 10 versus 5.6 % increase of HDL cholesterol. A population of 7,609 virtual subjects was generated using a Monte Carlo approach, and the response to a 40 mg/d pravastatin dose was simulated for each subject. Linear regression analysis of the pravastatin response in this virtual population showed that hepatic and peripheral cholesterol synthesis had the largest regression coefficients for the non-HDL-C response. However, the modeling also showed that these processes alone did not suffice to predict non-HDL-C response to pravastatin, contradicting the hypothesis that people with high cholesterol synthesis rates are good statin responders. In conclusion, we have developed a PBK model that is able to accurately describe the effect of pravastatin treatment on plasma cholesterol concentrations and can be used to provide insight in the mechanisms behind individual variation in statin response. © 2014 Springer Science+Business Media. Chemicals/CAS: cholesterol, 57-88-5; pravastatin, 81093-37-0, 81131-70-6