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Germovsek, E., Hansson, A., Kjellsson, M. C., Perez Ruixo, J. J., Westin, A., Soons, P. A., . . . Karlsson, M. (2020). Relating Nicotine Plasma Concentration to Momentary Craving Across Four Nicotine Replacement Therapy Formulations. Clinical Pharmacology and Therapeutics, 107(1), 238-245
Open this publication in new window or tab >>Relating Nicotine Plasma Concentration to Momentary Craving Across Four Nicotine Replacement Therapy Formulations
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2020 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 107, no 1, p. 238-245Article in journal (Refereed) Published
Abstract [en]

Tobacco use is a major health concern. To assist smoking cessation, nicotine replacement therapy (NRT) is used to reduce nicotine craving. We quantitatively described the relationship between nicotine pharmacokinetics (PKs) from NRTs and momentary craving, linking two different pharmacodynamic (PD) scales for measuring craving. The dataset comprised retrospective data from 17 clinical studies and included 1,077 adult smokers with 39,802 craving observations from four formulations: lozenge, gum, mouth spray, and patch. A PK/PD model was developed that linked individual predicted nicotine concentrations with the categorical and visual analogue PD scales through a joint bounded integer model. A maximum effect model, accounting for acute tolerance development, successfully related nicotine concentrations to momentary craving. Results showed that all formulations were similarly effective in reducing craving, albeit with a fourfold lower potency for the patch. Women were found to have a higher maximal effect of nicotine to reduce craving, compared with men.

Place, publisher, year, edition, pages
WILEY, 2020
National Category
Pharmacology and Toxicology
Identifiers
urn:nbn:se:uu:diva-408092 (URN)10.1002/cpt.1595 (DOI)000512979000045 ()31355455 (PubMedID)
Available from: 2020-04-04 Created: 2020-04-04 Last updated: 2020-04-04Bibliographically approved
Duthaler, U., Leisegang, R., Karlsson, M., Krähenbühl, S. & Hammann, F. (2020). The effect of food on the pharmacokinetics of oral ivermectin. Journal of Antimicrobial Chemotherapy, 75(2), 438-440
Open this publication in new window or tab >>The effect of food on the pharmacokinetics of oral ivermectin
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2020 (English)In: Journal of Antimicrobial Chemotherapy, ISSN 0305-7453, E-ISSN 1460-2091, Vol. 75, no 2, p. 438-440Article in journal (Refereed) Published
Abstract [en]

Background: Ivermectin is an older anthelminthic agent that is being studied more intensely given its potential for mass drug administration against scabies, malaria and other neglected tropical diseases. Its pharmacokinetics (PK) remain poorly characterized. Furthermore, the majority of PK trials are performed under fasted-state dosing conditions, and the effect of food is therefore not well known. To better plan and design field trials with ivermectin, a model that can account for both conditions would be valuable.

Objectives: To develop a PK model and characterize the food effect with single oral doses of ivermectin.

Patients and methods: We performed a population-based PK analysis of data pooled from two previous trials of a single dose of 12mg ivermectin, one with dosing after a high-fat breakfast (n=12) and one with fasted-state dosing (n=3).

Results: The final model described concentration-time profiles after fed and fasted dosing accurately, and estimated the food effect associated with relative bioavailability to 1.18 (95% CI 1.10-1.67).

Conclusions: In this analysis, the effect of a high-fat breakfast compared with a fasted-state administration of a single oral dose of 12mg ivermectin was minimal.

Place, publisher, year, edition, pages
OXFORD UNIV PRESS, 2020
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-407631 (URN)10.1093/jac/dkz466 (DOI)000515116900023 ()31691813 (PubMedID)
Available from: 2020-03-31 Created: 2020-03-31 Last updated: 2020-03-31Bibliographically approved
Tanneau, L., Karlsson, M. & Svensson, E. (2020). Understanding the drug exposure-response relationship of bedaquiline to predict efficacy for novel dosing regimens in the treatment of multidrug-resistant tuberculosis. British Journal of Clinical Pharmacology, 86(5), 913-922
Open this publication in new window or tab >>Understanding the drug exposure-response relationship of bedaquiline to predict efficacy for novel dosing regimens in the treatment of multidrug-resistant tuberculosis
2020 (English)In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 86, no 5, p. 913-922Article in journal (Refereed) Published
Abstract [en]

Aims: To externally validate an earlier characterized relationship between bedaquiline exposure and decline in bacterial load in a more difficult-to-treat patient population, and to explore the performances of alternative dosing regimens through simulations.

Methods: The bedaquiline exposure-response relationship was validated using time-to-positivity data from 233 newly diagnosed or treatment-experienced patients with drug-resistant tuberculosis from the C209 open-label study. The significance of the exposure-response relationship on the bacterial clearance was compared to a constant drug effect model. Tuberculosis resistance type and the presence and duration of antituberculosis pre-treatment were evaluated as additional covariates. Alternative dosing regimens were simulated for tuberculosis patients with different types of drug resistance.

Results: High bedaquiline concentrations were confirmed to be associated with faster bacterial load decline in patients, given that the exposure-effect relationship provided a significantly better fit than the constant drug effect (relative likelihood = 0.0003). The half-life of bacterial clearance was identified to be 22% longer in patients with pre-extensively drug-resistant (pre-XDR) tuberculosis (TB) and 86% longer in patients with extensively drug-resistant (XDR) TB, compared to patients with multidrug-resistant (MDR) TB. Achievement of the same treatment response for (pre-)XDR TB patients as for MDR TB patients would be possible by adjusting the dose and dosing frequency. Furthermore, daily bedaquiline administration as in the ZeNix regimen, was predicted to be as effective as the approved regimen.

Conclusion: The confirmed bedaquiline exposure-response relationship offers the possibility to predict efficacy under alternative dosing regimens, and provides a useful tool for potential treatment optimization.

Place, publisher, year, edition, pages
WILEY, 2020
Keywords
bedaquiline, modelling, multidrug-resistance, nonlinear mixed-effect, sputum culture conversion, time-to-positivity, tuberculosis
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-410904 (URN)10.1111/bcp.14199 (DOI)000526079500009 ()31840278 (PubMedID)
Funder
Swedish Research Council, 521-2011-3442EU, FP7, Seventh Framework Programme, FP7/2007-2013
Available from: 2020-05-25 Created: 2020-05-25 Last updated: 2020-05-25Bibliographically approved
Wellhagen, G. J., Kjellsson, M. C. & Karlsson, M. O. (2019). A Bounded Integer Model for Rating and Composite Scale Data. AAPS Journal, 21(4), Article ID 74.
Open this publication in new window or tab >>A Bounded Integer Model for Rating and Composite Scale Data
2019 (English)In: AAPS Journal, ISSN 1550-7416, E-ISSN 1550-7416, Vol. 21, no 4, article id 74Article in journal (Refereed) Published
Abstract [en]

Rating and composite scales are commonly used to assess treatment efficacy. The two main strategies for modelling such endpoints are to treat them as a continuous or an ordered categorical variable (CV or OC). Both strategies have disadvantages, including making assumptions that violate the integer nature of the data (CV) and requiring many parameters for scales with many response categories (OC). We present a method, called the bounded integer (BI) model, which utilises the probit function with fixed cut-offs to estimate the probability of a certain score through a latent variable. This method was successfully implemented to describe six data sets from four different therapeutic areas: Parkinson's disease, Alzheimer's disease, schizophrenia, and neuropathic pain. Five scales were investigated, ranging from 11 to 181 categories. The fit (likelihood) was better for the BI model than for corresponding OC or CV models (ΔAIC range 11-1555) in all cases but one (ΔAIC -63), while the number of parameters was the same or lower. Markovian elements were successfully implemented within the method. The performance in external validation, assessed through cross-validation, was also in favour of the new model (ΔOFV range 22-1694) except in one case (ΔOFV -70). A residual for diagnostic purposes is discussed. This study shows that the BI model respects the integer nature of data and is parsimonious in terms of number of estimated parameters.

Keywords
Bounded integer model, Categorical data, Composite scale, Nonlinear mixed-effects modelling, Probit regression, Rating scale
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-388766 (URN)10.1208/s12248-019-0343-9 (DOI)000470776700002 ()31172350 (PubMedID)
Funder
Swedish Research Council, 2018-03317
Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-08-12Bibliographically approved
Thorsted, A., Bouchene, S., Tano, E., Castegren, M., Lipcsey, M., Sjölin, J., . . . Nielsen, E. I. (2019). A non-linear mixed effect model for innate immune response: In vivo kinetics of endotoxin and its induction of the cytokines tumor necrosis factor alpha and interleukin-6. PLoS ONE, 14(2), Article ID e0211981.
Open this publication in new window or tab >>A non-linear mixed effect model for innate immune response: In vivo kinetics of endotoxin and its induction of the cytokines tumor necrosis factor alpha and interleukin-6
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2019 (English)In: PLoS ONE, E-ISSN 1932-6203, Vol. 14, no 2, article id e0211981Article in journal (Refereed) Published
Abstract [en]

Endotoxin, a component of the outer membrane of Gram-negative bacteria, has been extensively studied as a stimulator of the innate immune response. However, the temporal aspects and exposure-response relationship of endotoxin and resulting cytokine induction and tolerance development is less well defined. The aim of this work was to establish an in silico model that simultaneously captures and connects the in vivo time-courses of endotoxin, tumor necrosis factor alpha (TNF-alpha), interleukin-6 (IL-6), and associated tolerance development. Data from six studies of porcine endotoxemia in anesthetized piglets (n = 116) were combined and used in the analysis, with purified endotoxin (Escherichia coli O111: B4) being infused intravenously for 1-30 h in rates of 0.063-16.0 mu g/kg/h across studies. All data were modelled simultaneously by means of importance sampling in the non-linear mixed effects modelling software NONMEM. The infused endotoxin followed one-compartment disposition and non-linear elimination, and stimulated the production of TNF-alpha to describe the rapid increase in plasma concentration. Tolerance development, observed as declining TNF-alpha concentration with continued infusion of endotoxin, was also driven by endotoxin as a concentration-dependent increase in the potency parameter related to TNF-alpha production (EC50). Production of IL-6 was stimulated by both endotoxin and TNF-a, and four consecutive transit compartments described delayed increase in plasma IL-6. A model which simultaneously account for the time-courses of endotoxin and two immune response markers, the cytokines TNF-alpha and IL-6, as well as the development of endotoxin tolerance, was successfully established. This model-based approach is unique in its description of the time-courses and their interrelation and may be applied within research on immune response to bacterial endotoxin, or in pre-clinical pharmaceutical research when dealing with study design or translational aspects.

National Category
Physiology
Identifiers
urn:nbn:se:uu:diva-379038 (URN)10.1371/journal.pone.0211981 (DOI)000459330800014 ()30789941 (PubMedID)
Funder
Swedish Foundation for Strategic Research
Available from: 2019-03-11 Created: 2019-03-11 Last updated: 2020-04-16Bibliographically approved
Germovsek, E., Ambery, C., Yang, S., Beerahee, M., Karlsson, M. O. & Plan, E. L. (2019). A Novel Method for Analysing Frequent Observations from Questionnaires in Order to Model Patient-Reported Outcomes: Application to EXACT (R) Daily Diary Data from COPD Patients. AAPS Journal, 21(4), Article ID UNSP 60.
Open this publication in new window or tab >>A Novel Method for Analysing Frequent Observations from Questionnaires in Order to Model Patient-Reported Outcomes: Application to EXACT (R) Daily Diary Data from COPD Patients
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2019 (English)In: AAPS Journal, ISSN 1550-7416, E-ISSN 1550-7416, Vol. 21, no 4, article id UNSP 60Article in journal (Refereed) Published
Abstract [en]

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease with approximately 174 million cases worldwide. Electronic questionnaires are increasingly used for collecting patient-reported-outcome (PRO) data about disease symptoms. Our aim was to leverage PRO data, collected to record COPD disease symptoms, in a general modelling framework to enable interpretation of PRO observations in relation to disease progression and potential to predict exacerbations. The data were collected daily over a year, in a prospective, observational study. The e-questionnaire, the EXAcerbations of COPD Tool (EXACT (R)) included 14 items (i.e. questions) with 4 or 5 ordered categorical response options. An item response theory (IRT) model was used to relate the responses from each item to the underlying latent variable (which we refer to as disease severity), and on each item level, Markov models (MM) with 4 or 5 categories were applied to describe the dependence between consecutive observations. Minimal continuous time MMs were used and parameterised using ordinary differential equations. One hundred twenty-seven COPD patients were included (median age 67years, 54% male, 39% current smokers), providing approximately 40,000 observations per EXACT (R) item. The final model suggested that, with time, patients more often reported the same scores as the previous day, i.e. the scores were more stable. The modelled COPD disease severity change over time varied markedly between subjects, but was small in the typical individual. This is the first IRT model with Markovian properties; our analysis proved them necessary for predicting symptom-defined exacerbations.

Keywords
EXACT questionnaire, IRT, Markov model, NONMEM, PRO
National Category
Pharmacology and Toxicology
Identifiers
urn:nbn:se:uu:diva-383495 (URN)10.1208/s12248-019-0319-9 (DOI)000466176800001 ()31028495 (PubMedID)
Available from: 2019-05-17 Created: 2019-05-17 Last updated: 2019-05-17Bibliographically approved
Abrantes, J. A., Solms, A., Garmann, D., Nielsen, E. I., Jönsson, S. & Karlsson, M. (2019). Bayesian Forecasting Utilizing Bleeding Information to Support Dose Individualization of Factor VIII. CPT: Pharmacometrics & Systems Pharmacology, 8(12), 894-903
Open this publication in new window or tab >>Bayesian Forecasting Utilizing Bleeding Information to Support Dose Individualization of Factor VIII
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2019 (English)In: CPT: Pharmacometrics & Systems Pharmacology, ISSN 2163-8306, Vol. 8, no 12, p. 894-903Article in journal (Refereed) Published
Abstract [en]

Bayesian forecasting for dose individualization of prophylactic factor VIII replacement therapy using pharmacokinetic samples is challenged by large interindividual variability in the bleeding risk. A pharmacokinetic‐repeated time‐to‐event model‐based forecasting approach was developed to contrast the ability to predict the future occurrence of bleeds based on individual (i) pharmacokinetic, (ii) bleeding, and (iii) pharmacokinetic, bleeding and covariate information using observed data from the Long‐Term Efficacy Open‐Label Program in Severe Hemophilia A Disease (LEOPOLD) clinical trials (172 severe hemophilia A patients taking prophylactic treatment). The predictive performance assessed by the area under receiver operating characteristic (ROC) curves was 0.67 (95% confidence interval (CI), 0.65–0.69), 0.78 (95% CI, 0.76–0.80), and 0.79 (95% CI, 0.77–0.81) for patients ≥ 12 years when using pharmacokinetics, bleeds, and all data, respectively, suggesting that individual bleed information adds value to the optimization of prophylactic dosing regimens in severe hemophilia A. Further steps to optimize the proposed tool for factor VIII dose adaptation in the clinic are required.

National Category
Pharmacology and Toxicology
Identifiers
urn:nbn:se:uu:diva-381217 (URN)10.1002/psp4.12464 (DOI)000493314600001 ()31668021 (PubMedID)
Available from: 2019-04-05 Created: 2019-04-05 Last updated: 2020-04-20Bibliographically approved
Krause, A., Kloft, C., Huisinga, W., Karlsson, M., Pinheiro, J., Bies, R., . . . Musser, B. J. (2019). Comment on Jaki et al., A proposal for a new PhD level curriculum on quantitative methods for drug development. Pharmaceutical Statistics 17 (5):593-606, Sep/Oct 2018, DOI:10.1002/pst.1873 [Letter to the editor]. Pharmaceutical statistics, 18(3), 278-281
Open this publication in new window or tab >>Comment on Jaki et al., A proposal for a new PhD level curriculum on quantitative methods for drug development. Pharmaceutical Statistics 17 (5):593-606, Sep/Oct 2018, DOI:10.1002/pst.1873
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2019 (English)In: Pharmaceutical statistics, ISSN 1539-1604, E-ISSN 1539-1612, Vol. 18, no 3, p. 278-281Article in journal, Letter (Other academic) Published
Place, publisher, year, edition, pages
John Wiley & Sons, 2019
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-389924 (URN)10.1002/pst.1940 (DOI)000470930500001 ()30932340 (PubMedID)
Available from: 2019-08-01 Created: 2019-08-01 Last updated: 2019-08-01Bibliographically approved
Arshad, U., Chasseloup, E., Nordgren, R. & Karlsson, M. O. (2019). Development of visual predictive checks accounting for multimodal parameter distributions in mixture models. Journal of Pharmacokinetics and Pharmacodynamics, 46(3), 241-250
Open this publication in new window or tab >>Development of visual predictive checks accounting for multimodal parameter distributions in mixture models
2019 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 46, no 3, p. 241-250Article in journal (Refereed) Published
Abstract [en]

The assumption of interindividual variability being unimodally distributed in nonlinear mixed effects models does not hold when the population under study displays multimodal parameter distributions. Mixture models allow the identification of parameters characteristic to a subpopulation by describing these multimodalities. Visual predictive check (VPC) is a standard simulation based diagnostic tool, but not yet adapted to account for multimodal parameter distributions. Mixture model analysis provides the probability for an individual to belong to a subpopulation (IPmix) and the most likely subpopulation for an individual to belong to (MIXEST). Using simulated data examples, two implementation strategies were followed to split the data into subpopulations for the development of mixture model specific VPCs. The first strategy splits the observed and simulated data according to the MIXEST assignment. A shortcoming of the MIXEST-based allocation strategy was a biased allocation towards the dominating subpopulation. This shortcoming was avoided by splitting observed and simulated data according to the IPmix assignment. For illustration purpose, the approaches were also applied to an irinotecan mixture model demonstrating 36% lower clearance of irinotecan metabolite (SN-38) in individuals with UGT1A1 homo/heterozygote versus wild-type genotype. VPCs with segregated subpopulations were helpful in identifying model misspecifications which were not evident with standard VPCs. The new tool provides an enhanced power of evaluation of mixture models.

Place, publisher, year, edition, pages
SPRINGER/PLENUM PUBLISHERS, 2019
Keywords
Visual predictive checks, Mixture models, Multimodal parameter distributions, Pharmacokinetics, Pharmacodynamics
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-385960 (URN)10.1007/s10928-019-09632-9 (DOI)000468597100003 ()30968312 (PubMedID)
Available from: 2019-06-19 Created: 2019-06-19 Last updated: 2019-06-19Bibliographically approved
Schalkwijk, S., ter Heine, R., Colbers, A., Capparelli, E., Best, B. M., Cressey, T. R., . . . Burger, D. M. (2019). Evaluating darunavir/ritonavir dosing regimens for HIV-positive pregnant women using semi-mechanistic pharmacokinetic modelling. Journal of Antimicrobial Chemotherapy, 74(5), 1348-1356
Open this publication in new window or tab >>Evaluating darunavir/ritonavir dosing regimens for HIV-positive pregnant women using semi-mechanistic pharmacokinetic modelling
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2019 (English)In: Journal of Antimicrobial Chemotherapy, ISSN 0305-7453, E-ISSN 1460-2091, Vol. 74, no 5, p. 1348-1356Article in journal (Refereed) Published
Abstract [en]

Background: Darunavir 800mg once (q24h) or 600 mg twice (q12h) daily combined with low-dose ritonavir is used to treat HIV-positive pregnant women. Decreased total darunavir exposure (17%-50%) has been reported during pregnancy, but limited data on unbound exposure are available. Objectives: To evaluate total and unbound darunavir exposures following standard darunavir/ritonavir dosing and to explore the value of potential optimized darunavir/ritonavir dosing regimens for HIV-positive pregnant women. Patients and methods: A population pharmacokinetic analysis was conducted based on data from 85 women. The final model was used to simulate total and unbound darunavir AUC(0-tau) and C-trough during the third trimester of pregnancy, as well as to assess the probability of therapeutic exposure. Results: Simulations predicted that total darunavir exposure (AUC(0-tau)) was 24% and 23% lower in pregnancy for standard q24h and q12h dosing, respectively. Unbound darunavir AUC(0-tau) was 5% and 8% lower compared with post-partum for standard q24h and q12h dosing, respectively. The probability of therapeutic exposure (unbound) during pregnancy was higher for standard q12h dosing (99%) than for q24h dosing (94%). Conclusions: The standard q12h regimen resulted in maximal and higher rates of therapeutic exposure compared with standard q24h dosing. Darunavir/ritonavir 600/100 mg q12h should therefore be the preferred regimen during pregnancy unless (adherence) issues dictate q24h dosing. The value of alternative dosing regimens seems limited.

Place, publisher, year, edition, pages
OXFORD UNIV PRESS, 2019
National Category
Infectious Medicine
Identifiers
urn:nbn:se:uu:diva-393535 (URN)10.1093/jac/dky567 (DOI)000482043300029 ()30715324 (PubMedID)
Available from: 2019-09-24 Created: 2019-09-24 Last updated: 2019-09-24Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-1258-8297

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