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Using population pharmacokinetic analysis (PPK), we attempted to identify predictors of S-warfarin clearance (CL(S)) and to clarify population differences in S-warfarin pharmacokinetics among a cohort of 378 African American, Asian and white patients. Significant predictors of CL(S) included clinical (age, body weight and sex) and genotypic (CYP2C9*2,*3 and *8) factors, as well as African American ethnicity, the median CL(S) being 30% lower in the latter than in Asians and whites (170 versus 243 and 250 ml h(-1), P<0.01). The plasma S-warfarin (Cp(S)) time courses following the genotype-based dosing algorithms simulated using the PPK estimates showed African Americans with CYP2C9*1/*1 and any of the VKORC1 genotypes would have an average Cp(S) at steady state 1.5-1.8 times higher than in Asians and whites. These results indicate warfarin dosing algorithms should be evaluated in each respective ethnic population. Further study of a large African American cohort will be necessary to confirm the present findings.

The objective of the study was to update a previous NONMEM model to describe the relationship between warfarin dose and international normalized ratio (INR) response, to decrease the dependence of the model on pharmacokinetic (PK) data, and to improve the characterization of rare genotype combinations. The effects of age and CYP2C9 genotype on S-warfarin clearance were estimated from high-quality PK data. Thereafter, a temporal dose-response (K-PD) model was developed from information on dose, INR, age, and CYP2C9 and VKORC1 genotype, with drug clearance as a covariate. Two transit compartment chains accounted for the delay between exposure and response. CYP2C9 genotype was identified as the single most important predictor of required dose, causing a difference of up to 4.2-fold in the maintenance dose. VKORC1 accounted for a difference of up to 2.1-fold in dose, and age reduced the dose requirement by ~6% per decade. This reformulated K-PD model decreases dependence on PK data and enables robust assessment of INR response and dose predictions, even in individuals with rare genotype combinations.

The aim of this study was to characterize the relationship between warfarin concentrations and international normalized ratio (INR) response and to identify predictors important for dose individualization. S- and R-warfarin concentrations, INR, and CYP2C9 and VKORC1 genotypes from 150 patients were used to develop a population pharmacokinetic/pharmacodynamic model in NONMEM. The anticoagulant response was best described by an inhibitory E(MAX) model, with S-warfarin concentration as the only exposure predictor for response. Delay between exposure and response was accounted for by a transit compartment model with two parallel transit compartment chains. CYP2C9 genotype and age were identified as predictors for S-warfarin clearance, and VKORC1 genotype as a predictor for warfarin sensitivity. Predicted INR curves indicate important steady-state differences between patients with different sets of covariates; differences that cannot be foreseen from early INR assessments alone. It is important to account for CYP2C9 and VKORC1 genotypes and age to improve a priori and a posteriori individualization of warfarin therapy.