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  • 1.
    Abrantes, João A.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data2019In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 85, no 6, p. 1326-1336Article in journal (Refereed)
    Abstract [en]

    AIMS: This study aims to assess approaches to handle interoccasion variability (IOV) in a model-based therapeutic drug monitoring (TDM) context, using a population pharmacokinetic model of coagulation factor VIII as example.

    METHODS: We assessed five model-based TDM approaches: empirical Bayes estimates (EBEs) from a model including IOV, with individualized doses calculated based on individual parameters either (i) including or (ii) excluding variability related to IOV; and EBEs from a model excluding IOV by (iii) setting IOV to zero, (iv) summing variances of interindividual variability (IIV) and IOV into a single IIV term, or (v) re-estimating the model without IOV. The impact of varying IOV magnitudes (0-50%) and number of occasions/observations was explored. The approaches were compared with conventional weight-based dosing. Predictive performance was assessed with the prediction error (PE) percentiles.

    RESULTS: When IOV was lower than IIV, the accuracy was good for all approaches (50th percentile of the PE [P50] <7.4%), but the precision varied substantially between IOV magnitudes (P97.5 61-528%). Approach (ii) was the most precise forecasting method across a wide range of scenarios, particularly in case of sparse sampling or high magnitudes of IOV. Weight-based dosing led to less precise predictions than the model-based TDM approaches in most scenarios.

    CONCLUSIONS: Based on the studied scenarios and theoretical expectations, the best approach to handle IOV in model-based dose individualisation is to include IOV in the generation of the EBEs, but exclude the portion of unexplained variability related to IOV in the individual parameters used to calculate the future dose.

  • 2.
    Abrantes, João A.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala Univ, Dept Pharmaceut Biosci, Uppsala, Sweden..
    Korth-Bradley, J.
    Pfizer Inc, Collegeville, PA USA..
    Harnisch, L.
    Pfizer Ltd, Global Clin Pharmacol, Sandwich, Kent, England..
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Elucidation of Factor VIII Activity Pharmacokinetics: A Pooled Population Analysis in Patients With Hemophilia A Treated With Moroctocog Alfa2017In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 102, no 6, p. 977-988Article in journal (Refereed)
    Abstract [en]

    This study investigated the disposition of coagulation factor VIII activity in 754 patients with moderate to severe hemophilia A following the administration of moroctocog alfa, a B-domain deleted recombinant factor VIII. Data analyzed included patients aged 1 day to 73 years enrolled in 13 studies conducted over a period of 20 years in 25 countries. A two-compartment population pharmacokinetic model with a baseline model described the pooled data well. Body size, age, inhibitors, race, and analytical assay were identified as significant predictors of factor VIII disposition. In addition, simulations of prophylactic dosing schedules in several pediatric cohorts showed large variability and suggest that younger patients would require higher weight-adjusted doses than adolescents to achieve target factor VIII trough activity when receiving every other day or twice weekly dosing.

  • 3.
    Abrantes, João A.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Solms, Alexander
    Bayer, Berlin, Germany.
    Garmann, Dirk
    Bayer, Wuppertal, Germany.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Bayesian Forecasting Utilizing Bleeding Information to Support Dose Individualization of Factor VIIIIn: Article in journal (Refereed)
  • 4.
    Abrantes, João
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Solms, Alexander
    Bayer, Berlin, Germany.
    Garmann, Dirk
    Bayer, Wuppertal, Germany.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
    Relationship between factor VIII activity, bleeds and individual characteristics in severe hemophilia A patientsIn: Article in journal (Refereed)
  • 5.
    Acharya, Chayan
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Hooker, Andrew C.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Turkyilmaz, Gulbeyaz Yildiz
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Ege Univ, Fac Pharm, Dept Biopharmaceut & Pharmacokinet, TR-35100 Izmir, Turkey..
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    A diagnostic tool for population models using non-compartmental analysis: The ncappc package for R2016In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 127, p. 83-93Article in journal (Refereed)
    Abstract [en]

    Background and objective: Non-compartmental analysis (NCA) calculates pharmacokinetic (PK) metrics related to the systemic exposure to a drug following administration, e.g. area under the concentration time curve and peak concentration. We developed a new package in R, called ncappc, to perform (i) a NCA and (ii) simulation-based posterior predictive checks (ppc) for a population PK (PopPK) model using NCA metrics. Methods: The nca feature of ncappc package estimates the NCA metrics by NCA. The ppc feature of ncappc estimates the NCA metrics from multiple sets of simulated concentration time data and compares them with those estimated from the observed data. The diagnostic analysis is performed at the population as well as the individual level. The distribution of the simulated population means of each NCA metric is compared with the corresponding observed population mean. The individual level comparison is performed based on the deviation of the mean of any NCA metric based on simulations for an individual from the corresponding NCA metric obtained from the observed data. The ncappc package also reports the normalized prediction distribution error (NPDE) of the simulated NCA metrics for each individual and their distribution within a population. Results: The ncappc produces two default outputs depending on the type of analysis performed, i.e., NCA and PopPK diagnosis. The PopPK diagnosis feature of ncappc produces 8 sets of graphical outputs to assess the ability of a population model to simulate the concentration time profile of a drug and thereby evaluate model adequacy. In addition, tabular outputs are generated showing the values of the NCA metrics estimated from the observed and the simulated data, along with the deviation, NPDE, regression parameters used to estimate the elimination rate constant and the related population statistics. Conclusions: The ncappc package is a versatile and flexible tool-set written in R that successfully estimates NCA metrics from concentration time data and produces a comprehensive set of graphical and tabular output to summarize the diagnostic results including the model specific outliers. The output is easy to interpret and to use in evaluation of a population PK model. ncappc is freely available on CRAN (http://crantoprojectorg/web/packages/ncappc/index.html/) and GitHub (https://github.comicacha0227/ncappc/). 

  • 6.
    Björkman, Sven
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Folkesson, Anna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Pharmacokinetics and dose requirements of factor VIII over the age range 3-74 years: a population analysis based on 50 patients with long-term prophylactic treatment for haemophilia A2009In: European Journal of Clinical Pharmacology, ISSN 0031-6970, E-ISSN 1432-1041, Vol. 65, no 10, p. 989-998Article in journal (Refereed)
    Abstract [en]

    PURPOSE: The three aims of this investigation were (1) to develop a population pharmacokinetic (PK) model for factor VIII (FVIII) in haemophilia A patients, with estimates of inter-occasion and inter-individual variance, (2) to investigate whether appropriate dosing of FVIII for regular prophylaxis can be calculated according to patient characteristics, and (3) to present dosing recommendations for initiating prophylactic treatment. METHODS: A population PK model was developed using data from four PK studies on patients aged 7-74 years. The model was tested on sparse FVIII data from 42 outpatient visits by haemophilia prophylaxis patients aged 3-66 years. Dose requirements for prophylaxis were calculated both according to the population model and from empirical Bayesian estimates of FVIII PK in the individual patients. RESULTS: The study data were well characterised by a two-compartment PK model. Body weight, age and type of FVIII preparation (plasma-derived or recombinant) were identified as significant covariates. Inter-occasion variance was lower than inter-individual variance for both clearance and volume of the central compartment. The model could reasonably predict FVIII PK in the sparse clinical data. Model-predicted doses (based on age and body weight) to maintain a recommended 0.01 U/mL trough level of FVIII with administration on alternate days started at around 60 U/kg in the small children, decreasing to 10 U/kg or less in middle age. However, "true" dose requirements, as estimated from individual PK parameter data, showed a much greater variation. CONCLUSION: Appropriate dosing of FVIII for prophylactic treatment cannot be calculated only from body weight and/or age. However, plausible starting doses for most patients would be 1,000 U every other day. FVIII levels should then be checked for dose adjustment.

  • 7.
    Brekkan, Ari
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Berntorp, Erik
    Skane Univ Hosp, Clin Coagulat Res Unit, Malmo, Sweden.
    Jensen, Kirsten
    Skane Univ Hosp, Clin Coagulat Res Unit, Malmo, Sweden.
    Nielsen, Elisabet I
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Population Pharmacokinetics of Plasma-Derived Factor IX: Procedures for Dose Individualization2016In: Journal of Thrombosis and Haemostasis, ISSN 1538-7933, E-ISSN 1538-7836, Vol. 14, no 4, p. 724-732Article in journal (Refereed)
    Abstract [en]

    Background: Population pharmacokinetic (POPPK) models describing factor IX (FIX) activity levels in plasma, in combination with individual FIX measurements, may be used to individualize dosing in the treatment of hemophilia B. Objectives: The aim was to reevaluate a previously developed POPPK model for FIX activity and to explore the number and timing of FIX samples required in pharmacokinetic (PK) dose individualization. Methods: The POPPK model was reevaluated using an extended data set. Several sampling schedules, varying with respect to the timing and number of samples, were evaluated in a simulation study with relative dose errors compared between schedules. The performance of individually calculated doses was compared with commonly prescribed FIX doses with respect to the number of patients with a trough FIX activity > 0.01 U mL(-1). Results and conclusions: A three-compartment PK model best described the FIX activity levels. The number and timing of samples greatly influenced imprecision in dose prediction. Schedules with single samples taken on both day 2 and day 3 were identified as being convenient schedules with an acceptable performance level. Individually calculated doses performed better with respect to patient target attainment than a fixed 40 U kg(-1) dose regardless of how many samples were available to calculate individual doses. The results of this study suggest that PK dose tailoring with limited sampling may be applicable for plasma-derived FIX products.

  • 8.
    Brekkan, Ari
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Degerman, Johanna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Model-based evaluation of low dose factor VIII prophylaxis in haemophilia A2019In: Haemophilia, ISSN 1351-8216, E-ISSN 1365-2516, Vol. 25, no 3, p. 408-415Article in journal (Refereed)
    Abstract [en]

    Introduction The optimal treatment modality for haemophilia A is lifelong prophylaxis which is expensive and may not be implementable everywhere where factor VIII (FVIII) availability is limited. A less costly alternative to prophylaxis is low-dose prophylaxis (LDP) which was compared to conventional prophylaxis in this model-based simulation study. Aim To explore whether LDP is motivated where standard prophylaxis is not implementable, including evaluating LDP efficacy compared to high-dose prophylaxis and investigating the potential economic benefit of individualized dosing. Methods For a virtual adult haemophilia A population, FVIII activity levels were simulated following alternative treatment regimens, based on a published population PK model. The regimens included very LDP, LDP and conventional prophylaxis twice and thrice weekly. The annual probability of bleeding was predicted based on the weekly time spent below 1 IU/dL, using a previously published relationship. Additionally, PK-based dose individualization was evaluated to determine FVIII savings using Bayesian forecasting. Results A treatment regimen of 10 IU/kg administered thrice weekly cost 75% less than a standard high-dose regimen and was predicted to have a 5% higher median probability of annual bleeds. PK-based dose individualization may result in further cost-savings, but implementation needs benefit versus feasibility consideration. Conclusion Based on simulations, a promising LDP regimen was identified that decreased treatment costs compared with standard high-dose prophylaxis at a small increase in bleeding risk. The results indicate that LDP is advocated where the standard-of-care is on-demand treatment; however, the results should be considered in the context of any limitations of the applied models.

  • 9.
    Brekkan, Ari
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Hooker, Andrew
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Reduced and optimized trial designs for drugs described by a target mediated drug disposition model2018In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 45, no 4, p. 637-647Article in journal (Refereed)
    Abstract [en]

    Monoclonal antibodies against soluble targets are often rich and include the sampling of multiple analytes over a lengthy period of time. Predictive models built on data obtained in such studies can be useful in all drug development phases. If adequate model predictions can be maintained with a reduced design (e.g. fewer samples or shorter duration) the use of such designs may be advocated. The effect of reducing and optimizing a rich design based on a published study for Omalizumab (OMA) was evaluated as an example. OMA pharmacokinetics were characterized using a target-mediated drug disposition model considering the binding of OMA to free IgE and the subsequent formation of an OMA-IgE complex. The performance of the reduced and optimized designs was evaluated with respect to: efficiency, parameter uncertainty and predictions of free target. It was possible to reduce the number of samples in the study by 30% while still maintaining an efficiency of almost 90%. A reduction in sampling duration by two-thirds resulted in an efficiency of 75%. Omission of any analyte measurement or a reduction of the number of dose levels was detrimental to the efficiency of the designs (efficiency ae<currency> 51%). However, other metrics were, in some cases, relatively unaffected, showing that multiple metrics may be needed to obtain balanced assessments of design performance.

  • 10.
    Brekkan, Ari
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
    Plan, Elodie L.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Handling Underlying Discrete Variables with Bivariate Mixed Hidden-Markov Models in NONMEMManuscript (preprint) (Other academic)
  • 11.
    Brekkan, Ari
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Lledo-Garcia, Rocio
    Lacroix, Brigitte
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
    Plan, Elodie L.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Characterization of Anti-Drug Antibody Dynamics Using a Bivariate Mixed Hidden-Markov ModelManuscript (preprint) (Other academic)
  • 12. Fanta, Samuel
    et al.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
    Backman, Janne T
    Karlsson, Mats O
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
    Hoppu, Kalle
    Developmental pharmacokinetics of ciclosporin: a population pharmacokinetic study in paediatric renal transplant candidates2007In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 64, no 6, p. 772-784Article in journal (Refereed)
    Abstract [en]

    Aims

    To use population pharmacokinetic modelling to characterize the influence of developmental and demographic factors on the pharmacokinetic variability of ciclosporin.

    Methods

    Pharmacokinetic modelling was performed in NONMEM using a dataset comprising 162 pretransplant children, aged 0.36–17.5 years. Ciclosporin was given intravenously (3 mg kg−1) and orally (10 mg kg−1) on separate occasions followed by blood sampling for 24 h.

    Results

    A three-compartment model with first-order absorption without lag-time best described the pharmacokinetics of ciclosporin. The most important covariate affecting systemic clearance (CL) and distribution volume (V) was body weight (BW; scaled allometrically), responsible for a fourfold difference in uncorrected ciclosporin CL and a sixfold difference in ciclosporin V. The other significant covariates, haematocrit, plasma cholesterol and creatinine, were estimated to explain 20–30% of interindividual differences in CL and V of ciclosporin. No age-related changes in oral bioavailability or in BW-normalized V were seen. The BW-normalized CL (CL/BW) declined with age and prepubertal children (<8 years) had an approximately 25% higher CL/BW than did older children. Normalization of CL for allometric BW (BW3/4) removed its relationship to age.

    Conclusion

    The relationship between CL and allometric BW is consistent with a gradual reduction in relative liver size, until adult values, and a relatively constant CYP3A4 content in the liver from about 6–12 months of age to adulthood. Ciclosporin oral bioavailability, known previously to display large interindividual variability, is not influenced by age. These findings can enable better individualization of ciclosporin dosing in infants, children and adolescents.

  • 13.
    Frobel, Anne-Kristina
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Backman, Janne T.
    Hoppu, Kalle
    Qvist, Erik
    Seikku, Paula
    Jalanko, Hannu
    Holmberg, Christer
    Keizer, Ron J.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Fanta, Samuel
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    A time-to-event model for acute rejections in paediatric renal transplant recipients treated with ciclosporin A2013In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 76, no 4 SI, p. 603-615Article in journal (Refereed)
    Abstract [en]

    AimsCiclosporin A (CsA) dosing in immunosuppression after paediatric kidney transplantation remains challenging, and appropriate target CsA exposures (AUCs) are controversial. This study aimed to develop a time-to-first-acute rejection (AR) model and to explore predictive factors for therapy outcome. MethodsPatient records at the Children's Hospital in Helsinki, Finland, were analysed. A parametric survival model in NONMEM was used to describe the time to first AR. The influences of AUC and other covariates were explored using stepwise covariate modelling, bootstrap-stepwise covariate modelling and cross-validated stepwise covariate modelling. The clinical relevance of the effects was assessed with the time at which 90% of the patients were AR free (t(90)). ResultsData from 87 patients (0.7-19.8 years old, 54 experiencing an AR) were analysed. The baseline hazard was described with a function changing in steps over time. No statistically significant covariate effects were identified, a finding substantiated by all methods used. Thus, within the observed AUC range (90% interval 1.13-8.40hmgl(-1)), a rise in AUC was not found to increase protection from AR. Dialysis time, sex and baseline weight were potential covariates, but the predicted clinical relevance of their effects was low. For the strongest covariate, dialysis time, median t(90) was 5.8days (90% confidence interval 5.1-6.8) for long dialysis times (90th percentile) and 7.4days (6.4-11.7) for short dialysis times (10th percentile). ConclusionsA survival model with discrete time-varying hazards described the data. Within the observed range, AUC was not identified as a covariate. This feedback on clinical practice may help to avoid unnecessarily high CsA dosing in children.

  • 14. Hallén, I P
    et al.
    Jönsson, Siv
    Medical Products Agency.
    Karlsson, M O
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Oskarsson, A
    Toxicokinetics of lead in lactating and nonlactating mice.1996In: Toxicology and Applied Pharmacology, ISSN 0041-008X, E-ISSN 1096-0333, Vol. 136, no 2, p. 342-7Article in journal (Refereed)
    Abstract [en]

    Toxicokinetics of lead in lactating and nonlactating mice were studied after a single intravenous injection of 0.05 mg of lead (2.5 mCi 203Pb)/kg. Lead concentrations in blood, plasma, and milk were measured for 10 days following dosing. The volume of distribution based on plasma lead was more than two times larger in lactating than in nonlactating mice, 133 and 58 liter/kg, respectively. Plasma lead clearance in lactating mice was 4.25 liter/hr/kg compared with 1.07 liter/hr/kg in nonlactating mice. However, no such pronounced difference in blood lead clearance was found between the two groups, indicating that this parameter does not reveal the kinetic characteristics during lactation. Milk was found to be an additional route of excretion for lead. About 1/3 of the administered dose of lead was excreted in milk. Accordingly, milk clearance contributed to 1/3 of the total plasma clearance in the mice. The relationships of lead in plasma to lead in whole blood as well as lead in milk to lead in whole blood were nonlinear, with a relatively higher increase in plasma and in milk lead levels at higher blood lead levels. This nonlinearity may be explained by a reduced uptake of lead in erythrocytes as the lead binding sites of these cells become saturated. In lactating mice, the maximum binding capacity of lead in red blood cells was even lower than in nonlactating mice. Similar nonlinear relationship have have also been found in human studies although at much higher levels of lead in blood. The milk:plasma concentration ratio for lead was found to be between 50 and 100 after 24 hr, demonstrating a much more efficient excretion of lead into milk than what is known from human studies. Differences in the milk composition may be one explanation for the species differences in milk excretion of lead. The present study shows that physiological changes during lactation alter the pharmacokinetics of lead in mice.

  • 15. Jensen, Kirsten
    et al.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Berntorp, Erik
    Population pharmacokinetics of plasma-derived factor IX2014In: Haemophilia, ISSN 1351-8216, E-ISSN 1365-2516, Vol. 20, no S3, p. 80-80Article in journal (Other academic)
  • 16.
    Jönsson, Siv
    et al.
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Cheng, Yi-Fang
    Edenius, Charlotte
    Lees, Kennedy R
    Odergren, Tomas
    Karlsson, Mats O
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Population pharmacokinetic modelling and estimation of dosing strategy for NXY-059, a nitrone being developed for stroke.2005In: Clin Pharmacokinet, ISSN 0312-5963, Vol. 44, no 8, p. 863-78Article in journal (Refereed)
  • 17.
    Jönsson, Siv
    et al.
    Medical Products Agency, Uppsala, Sweden .
    Henningsson, Anja
    Edholm, Monica
    Salmonson, Tomas
    Contribution of modeling and simulation studies in the regulatory review: A European regulatory perspective2011In: Clinical Trial Simulations: Applications and trends / [ed] Kimko HHC, Peck CC, New York: Springer, 2011, p. 15-36Chapter in book (Refereed)
  • 18.
    Jönsson, Siv
    et al.
    Medical Products Agency, Uppsala.
    Henningsson, Anja
    Medical Products Agency, Uppsala.
    Edholm, Monica
    Medical Products Agency, Uppsala.
    Salmonson, Tomas
    Medical Products Agency, Uppsala.
    Role of modelling and simulation: a European regulatory perspective2012In: Clinical Pharmacokinetics, ISSN 0312-5963, E-ISSN 1179-1926, Vol. 51, no 2, p. 69-76Article in journal (Refereed)
    Abstract [en]

    Modelling and simulation (M&S) of clinical data, e.g. pharmacokinetic, pharmacodynamic and clinical endpoints, is a useful approach for more efficient interpretation of collected data and for extrapolation of knowledge to the entire target population. This type of documentation is included in the majority of marketing authorization applications for new medicinal products. This article summarizes the current status of regulatory review with respect to the role of M&S in Europe from the perspective of the Swedish Medical Products Agency. At present, regulatory bodies in Europe encourage the application of the M&S approach during drug development. However, there is a lack of consensus and transparent guidance documents. The main regulatory usage is in the evaluation of dose choices in sub-populations and as support for the dosing regimen in general. The regulatory review of conestat alfa illustrates how the dose recommendation was revised during the approval procedure based on M&S information. A survey of marketing authorization applications for new medicinal products approved in 2010 revealed that the use of the information gained from M&S documentation varies with respect to both regulatory review and the applicants' presentation of the data in the submitted dossier. Increased utilization and broadened application of M&S is anticipated in pharmaceutical development, where one area of focus is medicines for paediatric patients. Accordingly, the regulatory agencies will need to increase their capability to assess and utilize this type of information, and an interactive process among regulatory agencies is warranted to provide more unified regulatory assessment and guidance. Moreover, applicants are encouraged to expand on the usage of exposure-response models to map the systemic exposure range that yields safe and efficacious treatment and to improve the presentation of the gained knowledge in summary documents of the marketing authorization applications.

  • 19.
    Jönsson, Siv
    et al.
    Clinical Pharmacology, AstraZeneca R&D Södertälje.
    Jonsson, E Niclas
    Hoffmann-La Roche Ltd., PDMP Modelling and Simulation, Grenzacherstr 124, Bldg. 15/1.052, CH-4070 Basel, Switzerland.
    Timing and efficiency in population pharmacokinetics/pharmacodynamic data analysis projects2007In: Pharmacometrics: the science of quantitative pharmacology / [ed] Ette EI, Williams PJ, Hoboken, New Jesey: John Wiley & Sons, 2007, p. 287-302Chapter in book (Refereed)
  • 20.
    Jönsson, Siv
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
    Karlsson, Mats O
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
    A rational approach for selection of optimal covariate-based dosing strategies2003In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 73, no 1, p. 7-19Article in journal (Other academic)
    Abstract [en]

    BACKGROUND: At present, there is no rational approach for choosing a dosing strategy for individualization based on a covariate. An approach to use in establishment of an a priori dosing strategy for individualization is presented. Factors influencing the choice of such a dosing strategy are identified. METHODS: The approach requires definition of the following: target variable, seriousness of deviations from the target (ie, risk function), population model, covariate distributions, and constraints. Minimizing the total risk yields an optimal dosing strategy, estimated as dose sizes for different subpopulations and covariate cutoff values at which doses are increased or decreased. The method was illustrated with the use of simulated and real drug examples for the situation in which clearance is related to creatinine clearance. RESULTS: The estimated optimal cutoff(s) paralleled the median creatinine clearance in the population. The extent of variability in clearance explained by creatinine clearance was the main factor influencing the optimal ratios between adjacent dose sizes. An optimal dosing strategy was possible to estimate for the real drug. CONCLUSIONS: The method is simple to perform, although one difficulty lies in defining the target variable and risk function. Our results imply that commonly used constraints in dosing strategies based on renal function (ie, dose ratio of 2 and predetermined cutoffs) are nonoptimal in the sense we propose. Because an optimal dosing strategy may not be practical to use, the therapeutic cost that would result with any constraint can be assessed by comparison of the outcome after the desired and the optimal strategy.

  • 21.
    Jönsson, Siv
    et al.
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Estimation of dosing strategies aiming at maximizing utility or responder probability, using oxybutynin as an example drug.2005In: Eur J Pharm Sci, ISSN 0928-0987, Vol. 25, no 1, p. 123-32Article in journal (Refereed)
  • 22.
    Jönsson, Siv
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
    Kjellsson, Maria C.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
    Karlsson, Mats O.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
    Estimating bias in population parameters for some models for repeated measures ordinal data using NONMEM or NLMIXED2004In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 31, no 4, p. 299-320Article in journal (Refereed)
    Abstract [en]

    The application of proportional odds models to ordered categorical data using the mixed-effects modeling approach has become more frequently reported within the pharmacokinetic/pharmacodynamic area during the last decade. The aim of this paper was to investigate the bias in parameter estimates, when models for ordered categorical data were estimated using methods employing different approximations of the likelihood integral; the Laplacian approximation in NONMEM (without and with the centering option) and NLMIXED, and the Gaussian quadrature approximations in NLMIXED. In particular, we have focused on situations with non-even distributions of the response categories and the impact of interpatient variability. This is a Monte Carlo simulation study where original data sets were derived from a known model and fixed study design. The simulated response was a four-category variable on the ordinal scale with categories 0, 1, 2 and 3. The model used for simulation was fitted to each data set for assessment of bias. Also, simulations of new data based on estimated population parameters were performed to evaluate the usefulness of the estimated model. For the conditions tested, Gaussian quadrature performed without appreciable bias in parameter estimates. However, markedly biased parameter estimates were obtained using the Laplacian estimation method without the centering option, in particular when distributions of observations between response categories were skewed and when the interpatient variability was moderate to large. Simulations under the model could not mimic the original data when bias was present, but resulted in overestimation of rare events. The bias was considerably reduced when the centering option in NONMEM was used. The cause for the biased estimates appears to be related to the conditioning on uninformative and uncertain empirical Bayes estimate of interindividual random effects during the estimation, in conjunction with the normality assumption.

  • 23.
    Jönsson, Siv
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Simonsson, Ulrika S. H.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Miller, Raymond
    Daiichi Sankyo Pharma Dev, Edison, NJ USA..
    Karlsson, Mats O.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Population pharmacokinetics of edoxaban and its main metabolite in a dedicated renal impairment study2015In: Journal of clinical pharmacology, ISSN 0091-2700, E-ISSN 1552-4604, Vol. 55, no 11, p. 1268-1279Article in journal (Refereed)
    Abstract [en]

    A model characterizing the population pharmacokinetics (PK) of edoxaban and its major metabolite, M4, following a single oral dose of 15mg administered to subjects with varying kidney function was developed. Thirty-two subjects contributed with edoxaban plasma, edoxaban urine, and M4 plasma concentrations. Edoxaban urine concentrations allowed estimation of renal clearance, and high contribution of renal to total clearance enabled estimation of absolute oral bioavailability. A 2-compartment model with delayed absorption and elimination parameterized as renal clearance linearly related to creatinine clearance (CLcr) and nonrenal clearance forming M4 described edoxaban PK. The PK of M4 was described with a 1-compartment model. For a typical subject (70kg; CLcr, 100mL/min) bioavailability, clearance, and central and peripheral volume of distribution for edoxaban was estimated to 72.3%, 21.0 L/h, 95.4 L, and 54.3 L, respectively. For both edoxaban and M4, the model predicted systemic exposure to increase 57.0%, 35.0%, and 11.6% in a subject having CLcr of 30, 50, and 80mL/min, respectively, compared with a subject having a CLcr of 100mL/min. Concentration ratios (M4 over edoxaban) were predicted to vary with time after dose, but with minor influence of kidney function and body weight. Results were in agreement with previous analyses.

  • 24.
    Jönsson, Siv
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Yang, Shuying
    GlaxoSmithKline, London, England..
    Chen, Chao
    GlaxoSmithKline, London, England..
    Plan, Elodie L.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Sample size for detection of drug effect using item level and total score models for Unified Parkinson's Disease Rating Scale data2018In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 45, p. S106-S107Article in journal (Other academic)
  • 25.
    Kågedal, Matts
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. AstraZeneca R&D, SE-151 85 Södertälje, Sweden.
    Cselényi, Zsolt
    Nyberg, Svante
    AstraZeneca R&D, SE-151 85 Södertälje, Sweden.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Raboisson, Patrick
    Stenkrona, Per
    Hooker, Andrew C.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Non-linear mixed effects modelling of positron emission tomography data for simultaneous estimation of radioligand kinetics and occupancy in healthy volunteers2012In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 61, no 4, p. 849-856Article in journal (Refereed)
    Abstract [en]

    The aim of this work was to develop a model simultaneously estimating (11)C-AZD9272 radioligand kinetics and the relationship between plasma concentration of AZD9272 and receptor occupancy in the human brain.

    AZD9272 is a new chemical entity pharmacologically characterised as a noncompetitive antagonist at the metabotropic glutamate receptor subtype 5 (mGluR5). Positron emission tomography (PET) was used to measure the time course of ((11)C-AZD9272) in the brain. The study included PET measurements in six healthy volunteers where the radioligand was given as a tracer dose alone as well as post oral treatment with different doses of unlabelled AZD9272. Estimation of radioligand kinetics, including saturation of receptor binding was performed by use of non-linear mixed effects modelling. Data from the regions with the highest (ventral striatum) and lowest (cerebellum) radioligand concentrations were included in the analysis. It was assumed that the extent of non-displaceable brain uptake was the same in both regions while the rate of CNS uptake and the receptor density differed.

    The results of the analysis showed that AZD9272 binding at the receptor is saturable with an estimated plasma concentration corresponding to 50% occupancy of approximately 200nM. The density of the receptor binding sites was estimated to 800nM and 200nM in ventral striatum and cerebellum respectively. By simultaneously analysing data from several PET measurements and different brain regions in a non-linear mixed effects framework it was possible to estimate parameters of interest that would otherwise be difficult to quantify.

  • 26.
    Lindqvist, Annika
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Hammarlund-Udenaes, Margareta
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Exploring Factors Causing Low Brain penetration of the Opioid Peptide DAMGO through Experimental Methods and Modeling2016In: Molecular Pharmaceutics, ISSN 1543-8384, E-ISSN 1543-8392, Vol. 13, no 4, p. 1258-1266Article in journal (Refereed)
    Abstract [en]

    To advance the development of peptide analogues for improved treatment of pain, we need to learn more about the blood brain barrier transport of these substances. A low penetration into the brain, with an unbound brain to blood ratio, K-p,K-uu, of 0.08, is an important reason for the lack of effect of the enkephalin analogue DAMGO (H-Tyr-D-Ala-Gly-MePhe-Gly-ol) according to earlier findings. The aim of this study was to investigate the role of efflux transporters, metabolism in the brain, and/or elimination through interstitial fluid bulk flow for the brain exposure of DAMGO. The in vivo brain distribution of DAMGO was evaluated using microdialysis in the rat. Data were analyzed with population modeling which resulted in a clearance into the brain of 1.1 and an efflux clearance 14 mu L/min/g_brain. The efflux clearance was thus much higher than the bulk flow known from the literature. Coadministration with the efflux transporter inhibitors cyclosporin A and elacridar in vivo did not affect K-p,K-uu. The permeability of DAMGO in the Caco-2 assay was very low, of the same size as mannitol. The efflux ratio was <2 and not influenced by cyclosporin A or elacridar. These results indicate that the well-known efflux transporters Pgp and Bcrp are not responsible for the higher efflux of DAMGO, which opens up for an important role of other transporters at the BBB.

  • 27.
    Mangles, S.
    et al.
    Hampshire Hosp NHS Fdn Trust, Haemophilia Haemostasis & Thrombosis Ctr, Basingstoke, Hants, England.
    Rea, C.
    Hampshire Hosp NHS Fdn Trust, Haemophilia Haemostasis & Thrombosis Ctr, Basingstoke, Hants, England.
    Madan, B.
    St Thomas Hosp, Ctr Haemostasis & Thrombosis, London, England.
    Nielsen, Elisabet I.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Needham, J.
    Hampshire Hosp NHS Fdn Trust, Haemophilia Haemostasis & Thrombosis Ctr, Basingstoke, Hants, England.
    Collins, P. W.
    Univ Hosp Wales, Arthur Bloom Haemophilia Ctr, Cardiff, S Glam, Wales.
    Rangarajanl, S.
    Hampshire Hosp NHS Fdn Trust, Haemophilia Haemostasis & Thrombosis Ctr, Basingstoke, Hants, England.
    Real life experiences of a PK dosing study: Challenges and lessons learned2018In: Haemophilia, ISSN 1351-8216, E-ISSN 1365-2516, Vol. 24, no 3, p. E145-E148Article in journal (Other academic)
  • 28.
    Niebecker, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Miller, Raymond
    Nyberg, Joakim
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Krekels, Elke H J
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Simonsson, Ulrika S H
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism-the Hokusai-VTE phase 3 study2015In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 80, no 6, p. 1374-1387Article in journal (Refereed)
    Abstract [en]

    AIMS: This study characterized the population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism in the Hokusai-VTE phase 3 study. The impact of the protocol-specified 50% dose reductions applied to patients with body weight ≤ 60 kg, creatinine clearance (CLcr ) of 30 to 50 ml min(-1) or concomitant P-glycoprotein inhibitor on edoxaban exposure was assessed using simulations.

    METHODS: The sparse data from Hokusai-VTE, 9531 concentrations collected from 3707 patients, were pooled with data from 13 phase 1 studies. In the analysis, the covariate relationships used for dose reductions were estimated and differences between healthy subjects and patients as well as additional covariate effects of age, race and gender were explored based on statistical and clinical significance.

    RESULTS: A linear two-compartment model with first order absorption preceded by a lag time best described the data. Allometrically scaled body weight was included on disposition parameters. Apparent clearance was parameterized as non-renal and renal. The latter increased non-linearly with increasing CLcr . Compared with healthy volunteers, inter-compartmental clearance and the CLcr covariate effect were different in patients (+64.6% and +274%). Asian patients had a 22.6% increased apparent central volume of distribution. The effect of co-administration of P-glycoprotein inhibitors seen in phase 1 could not be confirmed in the phase 3 data. Model-based simulations revealed lower exposure in dose-reduced compared with non-dose-reduced patients.

    CONCLUSIONS: The adopted dose-reduction strategy resulted in reduced exposure compared with non-dose-reduced, thereby overcompensating for covariate effects. The clinical impact of these differences on safety and efficacy remains to be evaluated.

  • 29.
    Novakovic, Ana M.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Merck KGaA, Pharmacometry, Darmstadt, Germany.
    Thorsted, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Schindler, Emilie
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Munafo, A.
    Merck Inst Pharmacometr, Lausanne, Switzerland.
    Karlsson, Mats O
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Pharmacometric Analysis of the Relationship Between Absolute Lymphocyte Count and Expanded Disability Status Scale and Relapse Rate, Efficacy End Points, in Multiple Sclerosis Trials2018In: Journal of clinical pharmacology, ISSN 0091-2700, E-ISSN 1552-4604, Vol. 58, no 10, p. 1284-1294Article in journal (Refereed)
    Abstract [en]

    The aim of this work was to assess the relationship between the absolute lymphocyte count (ALC), and disability (as measured by the Expanded Disability Status Scale [EDSS]) and occurrence of relapses, 2 efficacy endpoints, respectively, in patients with remitting-relasping multiple sclerosis. Data for ALC, EDSS, and relapse rate were available from 1319 patients receiving placebo and/or cladribine tablets. Pharmacodynamic models were developed to characterize the time course of the endpoints. ALC-related measures were then evaluated as predictors of the efficacy endpoints. EDSS data were best fitted by a model where the logit-linear disease progression is affected by the dynamics of ALC change from baseline. Relapse rate data were best described by the Weibull hazard function, and the ALC change from baseline was also found to be a significant predictor of time to relapse. Presented models have shown that once cladribine exposure driven ALC-derived measures are included in the model, the need for drug effect components is of less importance (EDSS) or disappears (relapse rate). This simplifies the models and theoretically makes them mechanism specific rather than drug specific. Having a reliable mechanism-specific model would allow leveraging historical data across compounds, to support decision making in drug development and possibly shorten the time to market.

  • 30.
    Nyberg, Joakim
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Kristin E.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Yin, O. Q. P.
    Daiichi Sankyo Pharma Dev, Translat Med & Clin Pharmacol, Modeling & Simulat, Edison, NJ USA..
    Miller, R.
    Daiichi Sankyo Pharma Dev, Translat Med & Clin Pharmacol, Modeling & Simulat, Edison, NJ USA..
    Karlsson, Mats O.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Simonsson, Ulrika S. H.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Edoxaban Exposure-Response Analysis and Clinical Utility Index Assessment in Patients With Symptomatic Deep-Vein Thrombosis or Pulmonary Embolism2016In: CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, ISSN 2163-8306, Vol. 5, no 4, p. 222-232Article in journal (Refereed)
    Abstract [en]

    Edoxaban exposure-response relationships from the phase III study evaluating edoxaban for prevention and treatment of venous thromboembolism (VTE) in patients with acute deep vein thrombosis (DVT) and/or pulmonary embolism (PE) were assessed by parametric time-to-event analysis. Statistical significant exposure-response relationships were recurrent VTE with hazard ratio (HR) based on average edoxaban concentration at steady state (C-av) (HRCav) 50.98 (i.e., change in the HR with every 1 ng/mL increase of C-av); the composite of recurrent DVT and nonfatal PE with HRC(av)50.99; and the composite of recurrent DVT, nonfatal PE, and all-cause mortality HRC(av)50.98, and all death using maximal edoxaban concentration (C-max) with HR (C-max) 50.99. No statistical significant exposure-response relationships were found for clinically relevant bleeding or major adverse cardiovascular event. Results support the recommendation of once-daily edoxaban 60 mg, and a reduced 30 mg dose in patients with moderate renal impairment, body weight <= 60 kg, or use of P-glycoprotein inhibitors verapamil or quinidine.

  • 31.
    Oosten, Astrid W.
    et al.
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands..
    Abrantes, João A.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Univ Coimbra, Fac Pharm, Dept Pharmacol, Coimbra, Portugal.;Univ Coimbra, CNC Ctr Neurosci & Cell Biol, Coimbra, Portugal..
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    de Bruijn, Peter
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands..
    Kuip, Evelien J. M.
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands..
    Falcao, Amilcar
    Univ Coimbra, Fac Pharm, Dept Pharmacol, Coimbra, Portugal.;Univ Coimbra, CNC Ctr Neurosci & Cell Biol, Coimbra, Portugal..
    van der Rijt, Carin C. D.
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands.;Netherlands Comprehens Canc Org, Utrecht, Netherlands..
    Mathijssen, Ron H. J.
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands..
    Treatment with subcutaneous and transdermal fentanyl: results from a population pharmacokinetic study in cancer patients2016In: European Journal of Clinical Pharmacology, ISSN 0031-6970, E-ISSN 1432-1041, Vol. 72, no 4, p. 459-467Article in journal (Refereed)
    Abstract [en]

    Transdermal fentanyl is effective for the treatment of moderate to severe cancer-related pain but is unsuitable for fast titration. In this setting, continuous subcutaneous fentanyl may be used. As data on the pharmacokinetics of continuous subcutaneous fentanyl are lacking, we studied the pharmacokinetics of subcutaneous and transdermal fentanyl. Furthermore, we evaluated rotations from the subcutaneous to the transdermal route. Fifty-two patients treated with subcutaneous and/or transdermal fentanyl for moderate to severe cancer-related pain participated. A population pharmacokinetic model was developed and evaluated using non-linear mixed-effects modelling. For rotations from subcutaneous to transdermal fentanyl, a 1:1 dose conversion ratio was used while the subcutaneous infusion was continued for 12 h (with a 50 % tapering after 6 h). A 6-h scheme with 50 % tapering after 3 h was simulated using the final model. A one-compartment model with first-order elimination and separate first-order absorption processes for each route adequately described the data. The estimated apparent clearance of fentanyl was 49.6 L/h; the absorption rate constant for subcutaneous and transdermal fentanyl was 0.0358 and 0.0135 h(-1), respectively. Moderate to large inter-individual and inter-occasion variability was found. Around rotation from subcutaneous to transdermal fentanyl, measured and simulated plasma fentanyl concentrations rose and increasing side effects were observed. We describe the pharmacokinetics of subcutaneous and transdermal fentanyl in one patient cohort and report several findings that are relevant for clinical practice. Further research is warranted to study the optimal scheme for rotations from the subcutaneous to the transdermal route.

  • 32.
    Oosten, Astrid W
    et al.
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands.
    Abrantes, João A.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Matic, Maja
    Erasmus MC, Dept Clin Chem, Rotterdam, Netherlands.; Sophia Childrens Univ Hosp, Erasmus MC, Dept Pediat Surg, Rotterdam, Netherlands.
    van Schaik, Ron H N
    Erasmus MC, Dept Clin Chem, Rotterdam, Netherlands.
    de Bruijn, Peter
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands.
    van der Rijt, Carin C D
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands.; Netherlands Comprehens Canc Org, Utrecht, Netherlands.
    Mathijssen, Ron H J
    Erasmus MC Canc Inst, Dept Med Oncol, Groene Hilledijk 301, NL-3075 EA Rotterdam, Netherlands.
    A Prospective Population Pharmacokinetic Study on Morphine Metabolism in Cancer Patients.2017In: Clinical Pharmacokinetics, ISSN 0312-5963, E-ISSN 1179-1926, Vol. 56, no 7, p. 733-746Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Oral and subcutaneous morphine is widely used for the treatment of cancer-related pain; however, solid pharmacokinetic data on this practice are lacking. Furthermore, it is largely unknown which factors contribute to the variability in clearances of morphine and its metabolites and whether morphine clearance is related to treatment outcome.

    METHODS: Blood samples from 49 cancer patients treated with oral and/or subcutaneous morphine were prospectively collected and were used to develop a population pharmacokinetic model for morphine, morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G). The influence of age, gender, renal function and several polymorphisms possibly related to the pharmacokinetics of the three compounds was investigated. In addition, the relation between treatment failure and morphine and metabolite clearances was explored.

    RESULTS: A one-compartment model including an extensive first-pass effect adequately described the data of morphine and its metabolites. Estimated mean area under the plasma concentration-time curve (AUC) ratios following oral versus subcutaneous administration were: M3G/morphine 29.7:1 vs. 11.1:1; M6G/morphine 5.26:1 vs. 1.95:1; and M3G/M6G 5.65:1 vs. 5.70:1. Renal function was significantly correlated with clearance of the metabolites, which increased 0.602 L/h per every 10 mL/min/1.73 m(2) increase of estimated glomerular filtration rate (eGFR), reaching a plateau for eGFR >90 mL/min/1.73 m(2). The clearance of morphine or its metabolites was not found to be correlated with treatment failure.

    CONCLUSION: The influence of age-, gender- and pharmacokinetic-related polymorphisms was not identified on the pharmacokinetics of morphine. Clearance of morphine or its metabolites was not found to explain treatment outcome; however, large variations in plasma concentrations of morphine, M3G and M6G support further studies on the relation between plasma concentrations and treatment outcome. Dutch Trial Register ID: NTR4369.

  • 33.
    van der Wouden, C. H.
    et al.
    Leiden Univ, Dept Clin Pharm & Toxicol, Med Ctr, Leiden, Netherlands..
    Cambon-Thomsen, A.
    UMR Inserm U1027, Toulouse, France.;Univ Toulouse III Paul Sabatier, Toulouse, France..
    Cecchin, E.
    Natl Canc Inst, Ctr Riferimento Oncol, Expt & Clin Pharmacol, Aviano, Italy..
    Cheung, K. C.
    Royal Dutch Pharmacists Assoc KNMP, The Hague, Netherlands..
    Davila-Fajardo, C. L.
    Granada Univ Hosp, Inst Biomed Res, Dept Clin Pharm, Granada, Spain..
    Deneer, V. H.
    St Antonius Hosp, Dept Clin Pharm, Nieuwegein, Netherlands..
    Dolzan, V.
    Univ Ljubljana, Inst Biochem, Pharmacogenet Lab, Fac Med, Ljubljana, Slovenia..
    Ingelman-Sundberg, M.
    Karolinska Inst, Pharmacogenet Sect, Dept Physiol & Pharmacol, Stockholm, Sweden..
    Jönsson, Siv
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Karlsson, Mats O.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Kriek, M.
    Leiden Univ, Ctr Clin Genet, Med Ctr, Leiden, Netherlands..
    Mitropoulou, C.
    Golden Helix Fdn, London, England..
    Patrinos, G. P.
    Univ Patras, Sch Hlth Sci, Dept Pharm, Univ Campus, Patras, Greece..
    Pirmohamed, M.
    Royal Liverpool Univ Hosp, Dept Mol & Clin Pharmacol, Liverpool, Merseyside, England.;Univ Liverpool, Liverpool, Merseyside, England..
    Samwald, M.
    Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria..
    Schaeffeler, E.
    Dr Margarete Fischer Bosch Inst Clin Pharmacol, Stuttgart, Germany.;Univ Tubingen, Tubingen, Germany..
    Schwab, M.
    Dr Margarete Fischer Bosch Inst Clin Pharmacol, Stuttgart, Germany.;Univ Tubingen, Tubingen, Germany.;Univ Hosp Tubingen, Dept Clin Pharmacol, Tubingen, Germany.;Univ Tubingen, Dept Pharm & Biochem, Tubingen, Germany..
    Steinberger, D.
    Bio Logis Ctr Human Genet, Frankfurt, Germany..
    Stingl, J.
    Fed Inst Drugs & Med Devices, Div Res, Bonn, Germany..
    Sunder-Plassmann, G.
    Med Univ Vienna, Dept Internal Med 3, Div Nephrol & Dialysis, Vienna, Austria..
    Toffoli, G.
    Natl Canc Inst, Ctr Riferimento Oncol, Expt & Clin Pharmacol, Aviano, Italy..
    Turner, R. M.
    Royal Liverpool Univ Hosp, Dept Mol & Clin Pharmacol, Liverpool, Merseyside, England.;Univ Liverpool, Liverpool, Merseyside, England..
    Van Rhenen, Mh
    Royal Dutch Pharmacists Assoc KNMP, The Hague, Netherlands..
    Swen, J. J.
    Leiden Univ, Dept Clin Pharm & Toxicol, Med Ctr, Leiden, Netherlands..
    Guchelaar, H-J
    Leiden Univ, Dept Clin Pharm & Toxicol, Med Ctr, Leiden, Netherlands..
    Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium2017In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 101, no 3, p. 341-358Article in journal (Refereed)
    Abstract [en]

    Despite scientific and clinical advances in the field of pharmacogenomics (PGx), application into routine care remains limited. Opportunely, several implementation studies and programs have been initiated over recent years. This article presents an overview of these studies and identifies current research gaps. Importantly, one such gap is the undetermined collective clinical utility of implementing a panel of PGx-markers into routine care, because the evidence base is currently limited to specific, individual drug-gene pairs. The Ubiquitous Pharmacogenomics (U-PGx) Consortium, which has been funded by the European Commission's Horizon-2020 program, aims to address this unmet need. In a prospective, block-randomized, controlled clinical study (PREemptive Pharmacogenomic testing for prevention of Adverse drug REactions [PREPARE]), pre-emptive genotyping of a panel of clinically relevant PGx-markers, for which guidelines are available, will be implemented across healthcare institutions in seven European countries. The impact on patient outcomes and cost-effectiveness will be investigated. The program is unique in its multicenter, multigene, multidrug, multi-ethnic, and multi-healthcare system approach.

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