Papers by Anna-Karin Hamberg
European Journal of Clinical Pharmacology, Jan 11, 2013
Purpose Numerous studies have investigated causes of warfarin dose variability in adults, whereas... more Purpose 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. Method An adult population pharmacokinetic/pharmacodynamic (PK/PD) model for warfarin, with CYP2C9 and VKORC1 genotype, age and target international normalized ratio (INR) as dose predictors, was bridged to children using allometric scaling methods. Its predictive properties were evaluated in an external data set of children 0-18 years old, including comparison of dose prediction accuracy with three pharmacogenetics-based algorithms for children. Results Overall, the bridged model predicted INR response well in 64 warfarin-treated Swedish children (median age 4.3 years), but with a tendency to overpredict 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 %. Conclusion A mechanism-based population model developed on adult data provides a promising first step towards more individualized warfarin therapy in children.
British Journal of Haematology, Jul 18, 2012
Purpose Numerous studies have investigated causes of warfarin dose variability in adults, whereas... more Purpose 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. Method An adult population pharmacokinetic/pharmacodynamic (PK/PD) model for warfarin, with CYP2C9 and VKORC1 genotype, age and target international normalized ratio (INR) as dose predictors, was bridged to children using allometric scaling methods. Its predictive properties were evaluated in an external data set of children 0-18 years old, including comparison of dose prediction accuracy with three pharmacogenetics-based algorithms for children. Results Overall, the bridged model predicted INR response well in 64 warfarin-treated Swedish children (median age 4.3 years), but with a tendency to overpredict 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 %. Conclusion A mechanism-based population model developed on adult data provides a promising first step towards more individualized warfarin therapy in children.
European Journal of Clinical Pharmacology, Aug 10, 2013
British Journal of Clinical Pharmacology, Nov 8, 2022
Funding information c4c (conect4children) is a project funded by the Innovative Medicines Initiat... more Funding information c4c (conect4children) is a project funded by the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no. 777389. 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 one of the most widely used anticoagulants. Therapy is complicated by warfarin’s narr... more 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.
BMC Medical Informatics and Decision Making, Feb 7, 2015
Background: Warfarin is the most widely prescribed anticoagulant for the prevention and treatment... more Background: Warfarin is the most widely prescribed anticoagulant for the 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 tenfold difference in the dose required for adequate anticoagulation in adults. An optimal dose that leads to a favourable balance between the wanted antithrombotic effect and the risk of bleeding as measured by the prothrombin time International Normalised Ratio (INR) must be found for each patient. A model describing the time-course of the INR response can be used to aid dose selection before starting therapy (a priori dose prediction) and after therapy has been initiated (a posteriori dose revision). Results: In this paper we describe a warfarin decision support tool. It was transferred from a population PKPD-model for warfarin developed in NONMEM to a platform independent tool written in Java. The tool proved capable of solving a system of differential equations that represent the pharmacokinetics and pharmacodynamics of warfarin with a performance comparable to NONMEM. To estimate an a priori dose the user enters information on body weight, age, baseline and target INR, and optionally CYP2C9 and VKORC1 genotype. By adding information about previous doses and INR observations, the tool will suggest a new dose a posteriori through Bayesian forecasting. 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 fixed or an individualized loading-dose regimen. Conclusions: We believe that this type of mechanism-based decision support tool could be useful for initiating and maintaining warfarin therapy in the clinic. It will ensure more consistent dose adjustment practices between prescribers, and provide efficient and truly individualized warfarin dosing in both children and adults.
Frontiers in Genetics, Sep 14, 2022
Apixaban is a direct oral anticoagulant, a factor Xa inhibitor, used for the prevention of ischem... more 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.
Warfarin dose prediction in children using pharmacometric bridging- Comparison with published pha... more Warfarin dose prediction in children using pharmacometric bridging- Comparison with published pharmacogenetic dosing algorithms
British Journal of Clinical Pharmacology
Funding information c4c (conect4children) is a project funded by the Innovative Medicines Initiat... more Funding information c4c (conect4children) is a project funded by the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement no. 777389. 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.
Frontiers in Genetics, Sep 14, 2022
Apixaban is a direct oral anticoagulant, a factor Xa inhibitor, used for the prevention of ischem... more 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.
Clinical Pharmacology & Therapeutics, 2018
Warfarin dose prediction in children using pharmacometric bridging- Comparison with published pha... more Warfarin dose prediction in children using pharmacometric bridging- Comparison with published pharmacogenetic dosing algorithms
Warfarin dose prediction in children using pharmacometric bridging—comparison with published phar... more Warfarin dose prediction in children using pharmacometric bridging—comparison with published pharmacogenetic
Warfarin dose prediction in children using pharmacometric bridging- Comparison with published pha... more Warfarin dose prediction in children using pharmacometric bridging- Comparison with published pharmacogenetic dosing algorithms
Clinical pharmacology and therapeutics, 2007
The aim of this study was to characterize the relationship between warfarin concentrations and in... more 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 im...
Clinical Pharmacology & Therapeutics, 2010
The objective of the study was to update a previous NONMEM model to describe the relationship bet... more 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.
Scandinavian Journal of Infectious Diseases, 2006
On 2 earlier occasions, in 2002 and 2003, the Swedish Medical Products Agency (MPA) and the Swedi... more On 2 earlier occasions, in 2002 and 2003, the Swedish Medical Products Agency (MPA) and the Swedish Reference Group for Antiviral Therapy (RAV) have jointly publicized recommendations for the treatment of HIV infection. A working group from the same expert team that produced the 2002 report has now revised the text again. Since the publication of the last treatment recommendations, 4 new medicines have become available: emtricitabine, atazanavir, fosamprenavir, and enfuvirtid. The last-mentioned belongs to a new class of HIV medications called fusion inhibitors (Box 1). It is likely that tipranavir will also be on the market soon. Simultaneously, the drug zalcitabin has been deregistered. The following updated recommendations parallel the earlier ones, but increased knowledge allows us to be more specific in our recommendations. Thus, it is now suggested that the initial treatment for HIV infection consist of 2 nucleoside reverse transcriptase inhibitors (NRTIs) and 1 non-nucleoside reverse transcriptase inhibitor (NNRTI); or 2 NRTIs and 1 protease inhibitor (PI). In the group of the NRTIs, stavudine is no longer recommended for this purpose. In the NNRTI group, efavirenz should be preferred to nevirapine, except under special circumstances. Finally, PIs ought to be boosted with ritonavir (PI/r). Also new are recommendations regarding treatment choices for patients co-infected with hepatitis B virus (HBV) or tuberculosis (TB). As in the case of the previous publication, recommendations are evidence-graded in accordance with the Oxford Centre for Evidence Based Medicine, 2001 (see http://www.cebm.net/levels_of_evidence.asp#levels), and have been supplemented with references to newly-added sections and data not referred to in earlier background documentation.
Pharmacogenomics, 2014
Clinical factors, demographic variables and variations in two genes, CYP2C9 and VKORC1, have been... more Clinical factors, demographic variables and variations in two genes, CYP2C9 and VKORC1, have been shown to contribute to the variability in warfarin dose requirements among adult patients. Less is known about their relative importance for dose variability in children. A few small studies have been reported, but the results have been conflicting, especially regarding the impact of genotypes. In this article, we critically review published pharmacogenetic-based prediction models for warfarin dosing in children, and present results from a head-to-head comparison of predictive performance in a distinct cohort of warfarin-treated children. Finally we discuss what properties a prediction model should have, and what knowledge gaps need to be filled, to improve warfarin therapy in children of all ages.
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Papers by Anna-Karin Hamberg