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A Whole-Body Physiologically Based Pharmacokinetic Model for Colistin and Colistin Methanesulfonate in Rat
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
INSERM, U 1070, Pole Biol Sante, Poitiers, France;CHU Poitiers, Lab Toxicol & Pharmacocinet, Poitiers, France.
INSERM, U 1070, Pole Biol Sante, Poitiers, France;CHU Poitiers, Lab Toxicol & Pharmacocinet, Poitiers, France.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.ORCID iD: 0000-0002-2979-679X
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2018 (English)In: Basic & Clinical Pharmacology & Toxicology, ISSN 1742-7835, E-ISSN 1742-7843, Vol. 123, no 4, p. 407-422Article in journal (Refereed) Published
Abstract [en]

Colistin is a polymyxin antibiotic used to treat patients infected with multidrug-resistant Gram-negative bacteria (MDR-GNB). The objective of this work was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model to predict tissue distribution of colistin in rat. The distribution of a drug in a tissue is commonly characterized by its tissue-to-plasma partition coefficient, K-p. Colistin and its prodrug, colistin methanesulfonate (CMS) K-p priors, were measured experimentally from rat tissue homogenates or predicted in silico. The PK parameters of both compounds were estimated fitting invivo their plasma concentration-time profiles from six rats receiving an i.v. bolus of CMS. The variability in the data was quantified by applying a nonlinear mixed effect (NLME) modelling approach. A WB-PBPK model was developed assuming a well-stirred and perfusion-limited distribution in tissue compartments. Prior information on tissue distribution of colistin and CMS was investigated following three scenarios: K-p was estimated using in silico K-p priors (I) or K-p was estimated using experimental K-p priors (II) or K-p was fixed to the experimental values (III). The WB-PBPK model best described colistin and CMS plasma concentration-time profiles in scenario II. Colistin-predicted concentrations in kidneys in scenario II were higher than in other tissues, which was consistent with its large experimental K-p prior. This might be explained by a high affinity of colistin for renal parenchyma and active reabsorption into the proximal tubular cells. In contrast, renal accumulation of colistin was not predicted in scenario I. Colistin and CMS clearance estimates were in agreement with published values. The developed model suggests using experimental priors over in silico K-p priors for kidneys to provide a better prediction of colistin renal distribution. Such models might serve in drug development for interspecies scaling and investigate the impact of disease state on colistin disposition.

Place, publisher, year, edition, pages
2018. Vol. 123, no 4, p. 407-422
National Category
Pharmaceutical Sciences Pharmacology and Toxicology
Identifiers
URN: urn:nbn:se:uu:diva-366956DOI: 10.1111/bcpt.13026ISI: 000444538100004PubMedID: 29665289OAI: oai:DiVA.org:uu-366956DiVA, id: diva2:1266333
Funder
Swedish Foundation for Strategic Research EU, FP7, Seventh Framework Programme, Health-F3-2011-278348Available from: 2018-11-27 Created: 2018-11-27 Last updated: 2018-11-27Bibliographically approved

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Bouchene, SalimFriberg, Lena EKarlsson, Mats O

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