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Warfarin dose prediction in children using pharmacometric bridging: comparison with published pharmacogenetic dosing algorithms
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical pharmacogenomics and osteoporosis.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Barmhjärtcentrum, Skånes Universietessjukhus, Lund.
Drottnings Silvias Barnsjukhus, Sahlgrenska Universitetssjukhuset, Göteborg.
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2013 (English)In: European Journal of Clinical Pharmacology, ISSN 0031-6970, E-ISSN 1432-1041, Vol. 69, no 6, 1275-1283 p.Article in journal (Refereed) Published
Abstract [en]


Numerous studies have investigated causes of warfarin dose variability in adults whereas studies in children are limited both in numbers and size. Mechanism-based population modelling provides an opportunity to condense and propagate prior knowledge from one population to another. The main objectives with this study were to evaluate the predictive performance of a theoretically bridged adult warfarin model in children, and to compare accuracy in dose prediction relative to published warfarin algorithms for children.


An adult population PK/PD-model for warfarin, with CYP2C9 and VKORC1 genotype, age and target INR as dose predictors, was bridged to children using allometric scaling methods. Its predictive properties were evaluated in an external dataset of children 0-18 years old, including comparison of dose prediction accuracy with three pharmacogenetics-based algorithms for children.


Overall, the bridged model predicted INR response well in 64 warfarin treated Swedish children (median age 4.3 years), but with a tendency to over predict INR in children ≤ 2 years old. The bridged model predicted 20 of 49 children (41%) within ± 20% of actual maintenance dose (median age 7.2 years). In comparison the published dosing algorithms predicted 33-41% of the children within ± 20% of actual dose. Dose optimization with the bridged model based on up to three individual INR observations increased the proportion within ± 20% of actual dose to 70%.


A mechanism-based population model developed on adult data provides a promising first step towards more individualized warfarin therapy in children.

Place, publisher, year, edition, pages
2013. Vol. 69, no 6, 1275-1283 p.
Keyword [en]
PK/PD model, Population analysis, Warfarin, Dosing, Children, Genotype
National Category
Research subject
Clinical Pharmacology
URN: urn:nbn:se:uu:diva-197596DOI: 10.1007/s00228-012-1466-4ISI: 000318865600008OAI: oai:DiVA.org:uu-197596DiVA: diva2:613631
Swedish Heart Lung Foundation

Correction in: EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY  Volume: 69, Issue: 9, Pages: 1737-1737, DOI: 10.1007/s00228-013-1565-x

Available from: 2013-04-02 Created: 2013-03-29 Last updated: 2016-02-22Bibliographically approved
In thesis
1. Pharmacometric Models for Individualisation of Warfarin in Adults and Children
Open this publication in new window or tab >>Pharmacometric Models for Individualisation of Warfarin in Adults and Children
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Warfarin is one of the most widely used anticoagulants. Therapy is complicated by warfarin’s narrow therapeutic range and pronounced variability in individual dose requirements. Although warfarin therapy is uncommon in children, it is crucial for children with certain congenital or acquired heart diseases. Treatment in children is especially difficult due to the lack of i) a decision support tool for efficient and consistent dose adjustments, and ii) a flexible warfarin formulation for accurate and reproducible dosing.

The overall aim of this thesis was to develop a PKPD-based pharmacometric model for warfarin that describes the dose-response relationship over time, and to identify important predictors that influence individual dose requirements both in adults and children. Special emphasis was placed on investigating the contribution of genetic factors to the observed variability.

A clinically useful pharmacometric model for warfarin has been developed using NONMEM. The model has been successfully reformulated into a KPD-model that describes the relationship between warfarin dose and INR response, and that is applicable to both adults and children. From a clinical perspective, this is a very important change since it allows the use of information on dose and INR that is available routinely. The model incorporates both patient and clinical characteristics, such as age, weight, CYP2C9 and VKORC1 genotype, and baseline and target INR, for the prediction of an individualised starting dose. It also enables the use of information from previous doses and INR observations to further individualise the dose a posteriori using a Bayesian forecasting method.

The NONMEM model has been transferred to a user-friendly, platform independent tool to aid use in clinical practice. The tool can be used for a priori and a posteriori individualisation of warfarin therapy in both adults and children. The tool should ensure consistent dose adjustment practices, and provide more efficient individualisation of warfarin dosing in all patients, irrespective of age, body weight, CYP2C9 or VKORC1 genotype, baseline or target INR. The expected outcome is improved warfarin therapy compared with empirical dosing, with patients achieving a therapeutic and stable INR faster and avoiding high INRs that increase the risk of bleeding.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. 80 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 897
warfarin, pharmacokinetics, pharmacodynamics, pharmacometrics, pharmacogenetics, dose individualisation, children
National Category
Clinical Medicine
Research subject
Clinical Pharmacology
urn:nbn:se:uu:diva-197599 (URN)978-91-554-8653-2 (ISBN)
Public defence
2013-05-25, Auditorium Minus, Gustavianum, Akademigatan 3, Uppsala, 13:00 (English)
Swedish Heart Lung Foundation
Available from: 2013-05-02 Created: 2013-03-29 Last updated: 2013-08-30Bibliographically approved

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