A longitudinal model describing the relationship between warfarin dose and INR response taking CYP2C9, VKORC1 and age into account
AK Hamberg (1)(4), JD Lindh (2), M Wadelius (1), A Rane (2) ML Dahl (1), EN Jonsson (3)(5)
(1) Department of Medical Sciences, Clinical Pharmacology, Uppsala University Hospital, Uppsala, Sweden; (2) Division of Clinical Pharmacology, Karolinska University Hospital Huddinge, Stockholm, Sweden; (3) Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy, Uppsala University, Sweden; (4) NDA Regulatory Service AB, Upplands Väsby, Sweden; (5) Exprimo NV, Mechelen, Belgium
Objectives: To reformulate and update a previous NONMEM model [1] for the relationship between warfarin dose and INR response.
Methods: The analysis was performed in two steps. In the first step, the effect of CYP2C9 genotype and age on S-warfarin clearance was estimated from high quality single dose PK data from 57 patients included in a previous study [1]. In the second step, a K-PD model was developed based on warfarin dose, INR response, age, CYP2C9 and VKORC1 genotypes from the 57 patients and a subset of 139 patients from the Swedish WARG study enriched for rare genotypes [2]. The contribution of each CYP2C9 *1, *2 and *3 allele and VKORC1 rs9923231 (-1639 G>A) allele was estimated separately and combined to yield genotype effects. The variability in clearance due to CYP2C9 genotype and age was included as a covariate in the K-PD model as described by Jacqmin et al [3]. The remaining 1287 WARG patients were used for internal model validation.
Results: The final K-PD model accounted for the delay between exposure and INR response through two parallel transit compartment chains with 3 and 2 compartments each. The model described the data well, and passed internal validation tests. The EC50 parameter was related to the VKORC1 genotype. The effect of variant CYP2C9 genotypes on warfarin dose requirements was in good agreement with published data from a meta-analysis of thirty-nine studies with a total of 7907 patients [4].
Conclusions: The reformulated K-PD model reduces the need for PK data and enables robust assessment of INR response and dose predictions even in individuals with rare genotype combinations.
References:
[1] Hamberg AK et al. A PK-PD Model for predicting the impact of age, CYP2C9, and VKORC1 genotype on individualization of warfarin therapy. Clin Pharmacol Ther, 2007; 81: 529-538
[2] Wadelius M et al. The largest prospective warfarin-treated cohort supports genetic forecasting. Blood, 2009; 113: 784-92
[3] Jacqmin P et al. Modelling response time profiles in the absence of drug concentrations: definition and performance evaluation of the K-PD model. J Pharmacokinet. Pharmacodyn, 2007; 34: 57-85
[4] Lindh JD et al. Influence of CYP2C9 genotype on warfarin dose requirements - a systematic review and meta-analysis. Eur J Clin Pharmacol, 2008 Nov 25: Epub
