Literature DB >> 25155592

Development of a population pharmacokinetic model characterizing the tissue distribution of azithromycin in healthy subjects.

Songmao Zheng1, Peter Matzneller2, Markus Zeitlinger2, Stephan Schmidt3.   

Abstract

Recent clinical trials indicate that the use of azithromycin is associated with the emergence of macrolide resistance. The objective of our study was to simultaneously characterize free target site concentrations and correlate them with the MIC90s of clinically relevant pathogens. Azithromycin (500 mg once daily [QD]) was administered orally to 6 healthy male volunteers for 3 days. The free concentrations in the interstitial space fluid (ISF) of muscle and subcutaneous fat tissue as well as the total concentrations in plasma and polymorphonuclear leukocytes (PMLs) were determined on days 1, 3, 5, and 10. All concentrations were modeled simultaneously in NONMEM 7.2 using a tissue distribution model that accounts for nonlinear protein binding and ionization state at physiological pH. The model performance and parameter estimates were evaluated via goodness-of-fit plots and nonparametric bootstrap analysis. The model we developed described the concentrations at all sampling sites reasonably well and showed that the overall pharmacokinetics of azithromycin is driven by the release of the drug from acidic cell/tissue compartments. The model-predicted unionized azithromycin (AZM) concentrations in the cytosol of PMLs (6.0 ± 1.2 ng/ml) were comparable to the measured ISF concentrations in the muscle (8.7 ± 2.9 ng/ml) and subcutis (4.1 ± 2.4 ng/ml) on day 10, whereas the total PML concentrations were >1,000-fold higher (14,217 ± 2,810 ng/ml). The total plasma and free ISF concentrations were insufficient to exceed the MIC90s of the skin pathogens at all times. Our results indicate that the slow release of azithromycin from low pH tissue/cell compartments is responsible for the long terminal half-life of the drug and thus the extended period of time during which free concentrations reside at subinhibitory concentrations.
Copyright © 2014, American Society for Microbiology. All Rights Reserved.

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Year:  2014        PMID: 25155592      PMCID: PMC4249372          DOI: 10.1128/AAC.02904-14

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  54 in total

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Authors:  G W Amsden; A N Nafziger; G Foulds
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Authors:  S Ohkuma; B Poole
Journal:  Proc Natl Acad Sci U S A       Date:  1978-07       Impact factor: 11.205

4.  Interaction of the macrolide azithromycin with phospholipids. II. Biophysical and computer-aided conformational studies.

Authors:  J P Montenez; F Van Bambeke; J Piret; A Schanck; R Brasseur; P M Tulkens; M P Mingeot-Leclercq
Journal:  Eur J Pharmacol       Date:  1996-10-24       Impact factor: 4.432

5.  Blood, tissue, and intracellular concentrations of azithromycin during and after end of therapy.

Authors:  P Matzneller; S Krasniqi; M Kinzig; F Sörgel; S Hüttner; E Lackner; M Müller; M Zeitlinger
Journal:  Antimicrob Agents Chemother       Date:  2013-01-28       Impact factor: 5.191

6.  Influence of macrolide antibiotics on promotion of resistance in the oral flora of children.

Authors:  U Kastner; J P Guggenbichler
Journal:  Infection       Date:  2001-10       Impact factor: 3.553

7.  Intrapulmonary pharmacokinetics of azithromycin in healthy volunteers given five oral doses.

Authors:  K M Olsen; G San Pedro; L P Gann; P O Gubbins; D M Halinski; G D Campbell
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  13 in total

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5.  Azithromycin enhances anticancer activity of TRAIL by inhibiting autophagy and up-regulating the protein levels of DR4/5 in colon cancer cells in vitro and in vivo.

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Journal:  Cancer Commun (Lond)       Date:  2018-07-03

6.  Antibiotic Resistance of Campylobacter Species in a Pediatric Cohort Study.

Authors:  Francesca Schiaffino; Josh M Colston; Maribel Paredes-Olortegui; Ruthly François; Nora Pisanic; Rosa Burga; Pablo Peñataro-Yori; Margaret N Kosek
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7.  Pharmacokinetics of Macrolide Antibiotics and Transport into the Interstitial Fluid: Comparison among Erythromycin, Clarithromycin, and Azithromycin.

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8.  Investigational treatments for COVID-19 may increase ventricular arrhythmia risk through drug interactions.

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9.  Predictions of Systemic, Intracellular, and Lung Concentrations of Azithromycin With Different Dosing Regimens Used in COVID-19 Clinical Trials.

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10.  Investigational Treatments for COVID-19 may Increase Ventricular Arrhythmia Risk Through Drug Interactions.

Authors:  Meera Varshneya; Itziar Irurzun-Arana; Chiara Campana; Rafael Dariolli; Amy Gutierrez; Taylor K Pullinger; Eric A Sobie
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2021-02-11
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