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Apixaban is a direct oral anticoagulant, a factor Xa inhibitor, used for the prevention of ischemic stroke in patients with atrial fibrillation. Despite using recommended dosing a few patients might still experience bleeding or lack of efficacy that might be related to inappropriate drug exposure. We conducted a genome-wide association study using data from 1,325 participants in the pivotal phase three trial of apixaban with the aim to identify genetic factors affecting the pharmacokinetics of apixaban. A candidate gene analysis was also performed for pre-specified variants in ABCB1, ABCG2, CYP3A4, CYP3A5, and SULT1A1, with a subsequent analysis of all available polymorphisms within the candidate genes. Significant findings were further evaluated to assess a potential association with clinical outcome such as bleeding or thromboembolic events. No variant was consistently associated with an altered apixaban exposure on a genome-wide level. The candidate gene analyses showed a statistically significant association with a well-known variant in the drug transporter gene ABCG2 (c.421G > T, rs2231142). Patients carrying this variant had a higher exposure to apixaban [area under the curve (AUC), beta = 151 (95% CI 59-243), p = 0.001]. On average, heterozygotes displayed a 5% increase of AUC and homozygotes a 17% increase of AUC, compared with homozygotes for the wild-type allele. Bleeding or thromboembolic events were not significantly associated with ABCG2 rs2231142. This large genome-wide study demonstrates that genetic variation in the drug transporter gene ABCG2 is associated with the pharmacokinetics of apixaban. However, the influence of this finding on drug exposure was small, and further studies are needed to better understand whether it is of relevance for ischemic and bleeding events.

Pharmacometric modelling plays a key role in both the design and analysis of regulatory trials in paediatric drug development. Studies in adults provide a rich source of data to inform the paediatric investigation plans, including knowledge on drug pharmacokinetics (PK), safety and efficacy. In children, drug disposition differs widely from birth to adolescence but extrapolating adult to paediatric PK, safety and efficacy either with pharmacometric or physiologically based approaches can help design or in some cases reduce the need for clinical studies. Aspects to consider when extrapolating PK include the maturation of drug metabolizing enzyme expression, glomerular filtration, drug excretory systems, and the expression and activity of specific transporters in conjunction with other drug properties such as fraction unbound. Knowledge of these can be used to develop extrapolation tools such as allometric scaling plus maturation functions or physiologically based PK. PK/pharmacodynamic approaches and well-designed clinical trials in children are of key importance in paediatric drug development. In this white paper, state-of-the-art of current methods used for paediatric extrapolation will be discussed. This paper is part of a conect4children implementation of innovative methodologies including pharmacometric and physiologically based PK modelling in clinical trial design/paediatric drug development through dissemination of expertise and expert advice. The suggestions arising from this white paper should define a minimum set of standards in paediatric modelling and contribute to the regulatory science.

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.

AIMS: Although genetic, clinical and demographic factors have been shown to explain approximately half of the inter-individual variability in warfarin dose requirement in adults, less is known about causes of dose variability in children. This study aimed to identify and quantify major genetic, clinical and demographic sources of warfarin dose variability in children using modelling and simulation. METHODS: Clinical, demographic and genetic data from 163 children with a median age of 6.3 years (range 0.06-18.9 years), covering over 183 years of warfarin therapy and 6445 INR observations were used to update and optimise a published adult pharmacometric warfarin model for use in children. RESULTS: Genotype effects in children were found to be comparable to what has been reported for adults, with CYP2C9 explaining up to a 4-fold difference in dose (CYP2C9 *1/*1 vs. *3/*3) and VKORC1 explaining up to a 2-fold difference in dose (VKORC1 G/G vs. A/A), respectively. The relationship between bodyweight and warfarin dose was non-linear, with a 3-fold difference in dose for a 4-fold difference in bodyweight. In addition, age, baseline and target INR, and time since initiation of therapy, but not CYP4F2 genotype, had a significant impact on typical warfarin dose requirements in children. CONCLUSIONS: The updated model provides quantitative estimates of major clinical, demographic and genetic factors impacting warfarin dose variability in children. With this new knowledge more individualised dosing regimens can be developed and prospectively evaluated in the pursuit of improving both efficacy and safety of warfarin therapy in children.

A significant proportion of the interindividual variability in warfarin dose requirements can be explained on the basis of CYP2C9 and VKORC1 genotypes. We report the development of a novel pharmacogenetics-based 3-day warfarin initiation dose (ID) algorithm based on the International Warfarin Pharmacogenetics Consortium (IWPC) maintenance dose algorithm and the CYP2C9 genotype-based variance in warfarin half-life. The predictive value of the pharmacogenetics-based ID was assessed in a large cohort of 671 newly diagnosed patients with thromboembolic disorders who were about to commence anticoagulation therapy in accordance with standard induction regimens. In patients with mean international normalized ratio (INR)(days 4-7)>4.0 (n = 63) after warfarin initiation, the pharmacogenetics-based ID algorithm predicted a markedly lower dose requirement (median reduction = 4.2 mg), whereas in those with mean INR(days 4-7) < 2.0 (n = 145), the predicted dose requirement was very similar to that in the standard regimen. The use of a pharmacogenetics-based ID may avoid overshooting of INR in warfarin-sensitive patients without unduly affecting the time taken to reach target range in the majority of patients.

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.

It is difficult to predict anticoagulation response to warfarin in children mainly because of a wide inter-individual variability in warfarin dose requirement. The present study objective was to identify important predictors of dose in children and to optimize a previous NONMEM warfarin model for a priori and a posteriori dose and INR predictions in children. Data from 163 warfarin treated children with underlying heart disease (median age 6.3 years) were used. CYP2C9 and VKORC1 genotype caused up to 4-fold and 2-fold differences in warfarin dose requirement, respectively. Other important predictors of warfarin dose were bodyweight, age, baseline and target INR, and time since initiation of therapy with lower doses during the initiation. CYP4F2 genotype had only a marginal effect on dose. The present study findings will aid the development of a personalised approach to warfarin therapy in children, in the pursuit of improving both efficacy and safety of anticoagulation therapy.