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Pharmacokinetic Interactions for Drugs with a Long Half-Life-Evidence for the Need of Model-Based Analysis
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 Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Johns Hopkins Univ, Sch Med, Dept Med, Baltimore, MD 21205 USA..
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2016 (English)In: AAPS Journal, ISSN 1550-7416, E-ISSN 1550-7416, Vol. 18, no 1, 171-179 p.Article in journal (Refereed) PublishedText
Abstract [en]

Pharmacokinetic drug-drug interactions (DDIs) can lead to undesired drug exposure, resulting in insufficient efficacy or aggravated toxicity. Accurate quantification of DDIs is therefore crucial but may be difficult when full concentration-time profiles are problematic to obtain. We have compared non-compartmental analysis (NCA) and model-based predictions of DDIs for long half-life drugs by conducting simulation studies and reviewing published trials, using antituberculosis drug bedaquiline (BDQ) as a model compound. Furthermore, different DDI study designs were evaluated. A sequential design mimicking conducted trials and a population pharmacokinetic (PK) model of BDQ and the M2 metabolite were utilized in the simulations where five interaction scenarios from strong inhibition (clearance fivefold decreased) to strong induction (clearance fivefold increased) were evaluated. In trial simulations, NCA systematically under-predicted the DDIs' impact. The bias in average exposure was 29-96% for BDQ and 20-677% for M2. The model-based analysis generated unbiased predictions, and simultaneous fitting of metabolite data increased precision in DDI predictions. The discrepancy between the methods was also apparent for conducted trials, e.g., lopinavir/ritonavir was predicted to increased BDQ exposure 22% by NCA and 188% by model-based methods. In the design evaluation, studies with parallel designs were considered and shown to generally be inferior to sequential/cross-over designs. However, in the case of low inter-individual variability and no informative metabolite data, a prolonged parallel design could be favored. Model-based analysis for DDI assessments is preferable over NCA for victim drugs with a long half-life and should always be used when incomplete concentration-time profiles are part of the analysis.

Place, publisher, year, edition, pages
2016. Vol. 18, no 1, 171-179 p.
Keyword [en]
drug-drug interactions, long half-life, model-based analysis, non-compartmental analysis, pharmacokinetics
National Category
Pharmacology and Toxicology
URN: urn:nbn:se:uu:diva-275555DOI: 10.1208/s12248-015-9829-2ISI: 000367529900014OAI: oai:DiVA.org:uu-275555DiVA: diva2:900611
Swedish Research Council, 521-2011-3442EU, FP7, Seventh Framework Programme, FP7/2007-2013
Available from: 2016-02-04 Created: 2016-02-04 Last updated: 2016-05-12Bibliographically approved
In thesis
1. Pharmacometric Models to Improve Treatment of Tuberculosis
Open this publication in new window or tab >>Pharmacometric Models to Improve Treatment of Tuberculosis
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Tuberculosis (TB) is the world’s most deadly infectious disease and causes enormous public health problems. The comorbidity with HIV and the rise of multidrug-resistant TB strains impede successful therapy through drug-drug interactions and the lack of efficient second-line treatments. The aim of this thesis was to support the improvement of anti-TB therapy through development of pharmacometric models, specifically focusing on the novel drug bedaquiline, pharmacokinetic interactions and methods for pooled population analyses.

A population pharmacokinetic model of bedaquiline and its metabolite M2, linked to semi-mechanistic models of body weight and albumin concentrations, was developed and used for exposure-response analysis. Treatment response was quantified by measurements of mycobacterial load and early bedaquiline exposure was found to significantly impact the half-life of bacterial clearance. The analysis represents the first successful characterization of a concentration-effect relationship for bedaquiline.

Single-dose Phase I studies investigating potential interactions between bedaquiline and efavirenz, nevirapine, ritonavir-boosted lopinavir, rifampicin and rifapentine were analyzed with a model-based approach. Substantial effects were detected in several cases and dose-adjustments mitigating the impact were suggested after simulations. The interaction effects of nevirapine and ritonavir-boosted lopinavir were also confirmed in patients with multidrug-resistant TB on long-term treatment combining the antiretrovirals and bedaquiline. Furthermore, the outcomes from model-based analysis were compared to results from conventional non-compartmental analysis in a simulation study. Non-compartmental analysis was found to consistently underpredict the interaction effect when most of the concentration-time profile was not observed, as commonly is the case for compounds with very long terminal half-life such as bedaquiline.

To facilitate pooled analyses of individual patient data from multiple sources a structured development procedure was outlined and a fast diagnostic tool for extensions of the stochastic model components was developed. Pooled analyses of nevirapine and rifabutin pharmacokinetics were performed; the latter generating comprehensive dosing recommendations for combined administration of rifabutin and antiretroviral protease inhibitors.

The work presented in this thesis demonstrates the usefulness of pharmacometric techniques to improve treatment of TB and especially contributes evidence to inform optimized dosing regimens of new and old anti-TB drugs in various clinical contexts.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 79 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 214
pharmacokinetics, pharmacodynamics, population approach, nonlinear mixed-effects models, multidrug-resistant tuberculosis, bedaquiline, antiretroviral, drug-drug interactions, time-to-event, albumin
National Category
Medical and Health Sciences
Research subject
Clinical Pharmacology
urn:nbn:se:uu:diva-282139 (URN)978-91-554-9539-8 (ISBN)
Public defence
2016-05-20, B21, BMC, Husargatan 3, Uppsala, 09:15 (English)
Swedish Research Council, 521-2011-3442EU, FP7, Seventh Framework Programme, 115337EU, FP7, Seventh Framework Programme, 115156
Available from: 2016-04-28 Created: 2016-04-03 Last updated: 2016-05-12

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Svensson, Elin M.Karlsson, Mats O.
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