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Abrantes, J. A., Jönsson, S., Karlsson, M. & Nielsen, E. I. (2019). Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data. British Journal of Clinical Pharmacology, 85(6), 1326-1336
Open this publication in new window or tab >>Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data
2019 (English)In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 85, no 6, p. 1326-1336Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019
Keywords
NONMEM, pharmacokinetics, population analysis, therapeutic drug monitoring
National Category
Pharmacology and Toxicology
Identifiers
urn:nbn:se:uu:diva-381215 (URN)10.1111/bcp.13901 (DOI)000468974200029 ()30767254 (PubMedID)
Available from: 2019-04-05 Created: 2019-04-05 Last updated: 2019-06-24Bibliographically approved
Brekkan, A., Degerman, J. & Jönsson, S. (2019). Model-based evaluation of low dose factor VIII prophylaxis in haemophilia A. Haemophilia, 25(3), 408-415
Open this publication in new window or tab >>Model-based evaluation of low dose factor VIII prophylaxis in haemophilia A
2019 (English)In: Haemophilia, ISSN 1351-8216, E-ISSN 1365-2516, Vol. 25, no 3, p. 408-415Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019
Keywords
factor VIII prophylaxis, low‐dose prophylaxis, model simulations, population PK analysis
National Category
Hematology
Identifiers
urn:nbn:se:uu:diva-381430 (URN)10.1111/hae.13753 (DOI)000470929100026 ()31050134 (PubMedID)
Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-07-31Bibliographically approved
Novakovic, A. M., Thorsted, A., Schindler, E., Jönsson, S., Munafo, A. & Karlsson, M. O. (2018). Pharmacometric Analysis of the Relationship Between Absolute Lymphocyte Count and Expanded Disability Status Scale and Relapse Rate, Efficacy End Points, in Multiple Sclerosis Trials. Journal of clinical pharmacology, 58(10), 1284-1294
Open this publication in new window or tab >>Pharmacometric Analysis of the Relationship Between Absolute Lymphocyte Count and Expanded Disability Status Scale and Relapse Rate, Efficacy End Points, in Multiple Sclerosis Trials
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2018 (English)In: Journal of clinical pharmacology, ISSN 0091-2700, E-ISSN 1552-4604, Vol. 58, no 10, p. 1284-1294Article in journal (Refereed) Published
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.

Keywords
EDSS, lymphocytes, multiple sclerosis, pharmacometrics, relapses
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-364141 (URN)10.1002/jcph.1136 (DOI)000443590000006 ()29746722 (PubMedID)
Funder
EU, FP7, Seventh Framework Programme
Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2018-11-01Bibliographically approved
Mangles, S., Rea, C., Madan, B., Nielsen, E. I., Jönsson, S., Needham, J., . . . Rangarajanl, S. (2018). Real life experiences of a PK dosing study: Challenges and lessons learned [Letter to the editor]. Haemophilia, 24(3), E145-E148
Open this publication in new window or tab >>Real life experiences of a PK dosing study: Challenges and lessons learned
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2018 (English)In: Haemophilia, ISSN 1351-8216, E-ISSN 1365-2516, Vol. 24, no 3, p. E145-E148Article in journal, Letter (Other academic) Published
Place, publisher, year, edition, pages
John Wiley & Sons, 2018
National Category
Hematology
Identifiers
urn:nbn:se:uu:diva-366682 (URN)10.1111/hae.13470 (DOI)000434111800017 ()29626381 (PubMedID)
Available from: 2018-11-23 Created: 2018-11-23 Last updated: 2018-11-23Bibliographically approved
Brekkan, A., Jönsson, S., Karlsson, M. O. & Hooker, A. (2018). Reduced and optimized trial designs for drugs described by a target mediated drug disposition model. Journal of Pharmacokinetics and Pharmacodynamics, 45(4), 637-647
Open this publication in new window or tab >>Reduced and optimized trial designs for drugs described by a target mediated drug disposition model
2018 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 45, no 4, p. 637-647Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
SPRINGER/PLENUM PUBLISHERS, 2018
Keywords
Optimal design, Target mediated drug disposition, Monoclonal antibodies, Sampling time optimization, Model-based
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-361677 (URN)10.1007/s10928-018-9594-9 (DOI)000438685100008 ()29948794 (PubMedID)
Available from: 2018-10-05 Created: 2018-10-05 Last updated: 2019-04-11Bibliographically approved
Jönsson, S., Yang, S., Chen, C., Plan, E. L. & Karlsson, M. O. (2018). Sample size for detection of drug effect using item level and total score models for Unified Parkinson's Disease Rating Scale data. Journal of Pharmacokinetics and Pharmacodynamics, 45, S106-S107
Open this publication in new window or tab >>Sample size for detection of drug effect using item level and total score models for Unified Parkinson's Disease Rating Scale data
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2018 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 45, p. S106-S107Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
SPRINGER/PLENUM PUBLISHERS, 2018
National Category
Pharmacology and Toxicology
Identifiers
urn:nbn:se:uu:diva-365110 (URN)000445374700235 ()
Available from: 2018-11-15 Created: 2018-11-15 Last updated: 2018-11-15Bibliographically approved
Oosten, A. W., Abrantes, J. A., Jönsson, S., Matic, M., van Schaik, R. H., de Bruijn, P., . . . Mathijssen, R. H. (2017). A Prospective Population Pharmacokinetic Study on Morphine Metabolism in Cancer Patients.. Clinical Pharmacokinetics, 56(7), 733-746
Open this publication in new window or tab >>A Prospective Population Pharmacokinetic Study on Morphine Metabolism in Cancer Patients.
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2017 (English)In: Clinical Pharmacokinetics, ISSN 0312-5963, E-ISSN 1179-1926, Vol. 56, no 7, p. 733-746Article in journal (Refereed) Published
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.

National Category
Clinical Medicine
Identifiers
urn:nbn:se:uu:diva-318992 (URN)10.1007/s40262-016-0471-7 (DOI)000403686200005 ()27815868 (PubMedID)
Note

De två första författarna delar förstaförfattarskapet.

Available from: 2017-03-30 Created: 2017-03-30 Last updated: 2017-09-14Bibliographically approved
Abrantes, J. A., Nielsen, E. I., Korth-Bradley, J., Harnisch, L. & Jönsson, S. (2017). Elucidation of Factor VIII Activity Pharmacokinetics: A Pooled Population Analysis in Patients With Hemophilia A Treated With Moroctocog Alfa. Clinical Pharmacology and Therapeutics, 102(6), 977-988
Open this publication in new window or tab >>Elucidation of Factor VIII Activity Pharmacokinetics: A Pooled Population Analysis in Patients With Hemophilia A Treated With Moroctocog Alfa
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2017 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 102, no 6, p. 977-988Article in journal (Refereed) Published
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.

National Category
Pharmacology and Toxicology
Identifiers
urn:nbn:se:uu:diva-342208 (URN)10.1002/cpt.716 (DOI)000414921800026 ()28437834 (PubMedID)
Available from: 2018-02-20 Created: 2018-02-20 Last updated: 2019-04-05Bibliographically approved
van der Wouden, C. H., Cambon-Thomsen, A., Cecchin, E., Cheung, K. C., Davila-Fajardo, C. L., Deneer, V. H., . . . Guchelaar, H.-J. (2017). Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium. Clinical Pharmacology and Therapeutics, 101(3), 341-358
Open this publication in new window or tab >>Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium
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2017 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 101, no 3, p. 341-358Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
WILEY, 2017
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-320349 (URN)10.1002/cpt.602 (DOI)000396840700012 ()28027596 (PubMedID)
Funder
EU, European Research Council, 668353
Available from: 2017-04-19 Created: 2017-04-19 Last updated: 2018-01-13Bibliographically approved
Acharya, C., Hooker, A. C., Turkyilmaz, G. Y., Jönsson, S. & Karlsson, M. O. (2016). A diagnostic tool for population models using non-compartmental analysis: The ncappc package for R. Computer Methods and Programs in Biomedicine, 127, 83-93
Open this publication in new window or tab >>A diagnostic tool for population models using non-compartmental analysis: The ncappc package for R
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2016 (English)In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 127, p. 83-93Article in journal (Refereed) Published
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/). 

Keywords
Non-compartmental analysis (NCA), PK, NONMEM, Posterior predictive check, Simulation-based diagnostic
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-286630 (URN)10.1016/j.cmpb.2016.01.013 (DOI)000372521500008 ()27000291 (PubMedID)
Available from: 2016-04-28 Created: 2016-04-21 Last updated: 2017-11-30Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8240-0865

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