A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children

Warfarin is the most widely prescribed anticoagulant for prevention and treatment of thromboembolic events. Although highly effective, the use of warfarin is limited by a narrow therapeutic range combined with a more than ten-fold difference in the dose required for adequate anticoagulation in adults. For each patient, an optimal dose that leads to a favourable balance between the wanted antithrombotic effect and the risk of bleeding, measured as the prothrombin time International Normalised Ratio (INR), must be found. A model capable of describing the time-course of the INR response to warfarin therapy can be used to aid dose selection, both before starting therapy (a priori dose prediction) and after therapy has been initiated (a posteriori dose revision). In this paper we describe the transfer of a population PKPD-model for warfarin developed in NONMEM to a platform independent decision support tool written in Java. The tool proved capable of solving a system of differential equations representing the pharmacokinetics and pharmacodynamics of warfarin, with a performance comparable to NONMEM. To estimate an a priori dose the user provides information on body weight, age, CYP2C9 and VKORC1 genotype, baseline and target INR. With addition of information about previous doses and INR observations, the tool will use a Bayesian forecasting method to suggest an a posteriori dose, i.e. the dose with the highest probability to result in the desired INR. Results are displayed as the predicted dose per day and per week, and graphically as the predicted INR curve. The tool can also be used to predict INR following any given dose regimen, e.g. a loading-dose regimen. We believe it will provide a clinically useful tool for initiating and maintaining warfarin therapy in the clinic. It will ensure consistent dose adjustment practices between prescribers, and provide more efficient individualization of warfarin dosing in both children and adults