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Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models

INTRODUCTION: Ex vivo experiments in extracorporeal membrane oxygenation (ECMO) circuits have identified octanol-water partition coefficient (logP, a marker of lipophilicity) and protein binding (PB) as key drug factors affecting pharmacokinetics (PK) during ECMO. Using ovine models, in this study w...

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Autores principales: Shekar, Kiran, Roberts, Jason A., Barnett, Adrian G., Diab, Sara, Wallis, Steven C., Fung, Yoke L., Fraser, John F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4699331/
https://www.ncbi.nlm.nih.gov/pubmed/26667471
http://dx.doi.org/10.1186/s13054-015-1151-y
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author Shekar, Kiran
Roberts, Jason A.
Barnett, Adrian G.
Diab, Sara
Wallis, Steven C.
Fung, Yoke L.
Fraser, John F.
author_facet Shekar, Kiran
Roberts, Jason A.
Barnett, Adrian G.
Diab, Sara
Wallis, Steven C.
Fung, Yoke L.
Fraser, John F.
author_sort Shekar, Kiran
collection PubMed
description INTRODUCTION: Ex vivo experiments in extracorporeal membrane oxygenation (ECMO) circuits have identified octanol-water partition coefficient (logP, a marker of lipophilicity) and protein binding (PB) as key drug factors affecting pharmacokinetics (PK) during ECMO. Using ovine models, in this study we investigated whether these drug properties can be used to predict PK alterations of antimicrobial drugs during ECMO. METHODS: Single-dose PK sampling was performed in healthy sheep (HS, n = 7), healthy sheep on ECMO (E24H, n = 7) and sheep with smoke inhalation acute lung injury on ECMO (SE24H, n = 6). The sheep received eight study antimicrobials (ceftriaxone, gentamicin, meropenem, vancomycin, doripenem, ciprofloxacin, fluconazole, caspofungin) that exhibit varying degrees of logP and PB. Plasma drug concentrations were determined using validated chromatographic techniques. PK data obtained from a non-compartmental analysis were used in a linear regression model to predict PK parameters based on logP and PB. RESULTS: We found statistically significant differences in pH, haemodynamics, fluid balance and plasma proteins between the E24H and SE24H groups (p < 0.001). logP had a strong positive linear relationship with steady-state volume of distribution (V(ss)) in both the E24H and SE24H groups (p < 0.001) but not in the HS group (p = 0.9) and no relationship with clearance (CL) in all study groups. Although we observed an increase in CL for highly PB drugs in ECMO sheep, PB exhibited a weaker negative linear relationship with both CL (HS, p = 0.01; E24H, p < 0.001; SE24H, p < 0.001) and V(ss) (HS, p = 0.01; E24H, p = 0.004; SE24H, p =0.05) in the final model. CONCLUSIONS: Lipophilic antimicrobials are likely to have an increased V(ss) and decreased CL during ECMO. Protein-bound antimicrobial agents are likely to have reductions both in CL and V(ss) during ECMO. The strong relationship between lipophilicity and V(ss) seen in both the E24H and SE24H groups indicates circuit sequestration of lipophilic drugs. These findings highlight the importance of drug factors in predicting antimicrobial drug PK during ECMO and should be a consideration when performing and interpreting population PK studies.
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spelling pubmed-46993312016-01-05 Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models Shekar, Kiran Roberts, Jason A. Barnett, Adrian G. Diab, Sara Wallis, Steven C. Fung, Yoke L. Fraser, John F. Crit Care Research INTRODUCTION: Ex vivo experiments in extracorporeal membrane oxygenation (ECMO) circuits have identified octanol-water partition coefficient (logP, a marker of lipophilicity) and protein binding (PB) as key drug factors affecting pharmacokinetics (PK) during ECMO. Using ovine models, in this study we investigated whether these drug properties can be used to predict PK alterations of antimicrobial drugs during ECMO. METHODS: Single-dose PK sampling was performed in healthy sheep (HS, n = 7), healthy sheep on ECMO (E24H, n = 7) and sheep with smoke inhalation acute lung injury on ECMO (SE24H, n = 6). The sheep received eight study antimicrobials (ceftriaxone, gentamicin, meropenem, vancomycin, doripenem, ciprofloxacin, fluconazole, caspofungin) that exhibit varying degrees of logP and PB. Plasma drug concentrations were determined using validated chromatographic techniques. PK data obtained from a non-compartmental analysis were used in a linear regression model to predict PK parameters based on logP and PB. RESULTS: We found statistically significant differences in pH, haemodynamics, fluid balance and plasma proteins between the E24H and SE24H groups (p < 0.001). logP had a strong positive linear relationship with steady-state volume of distribution (V(ss)) in both the E24H and SE24H groups (p < 0.001) but not in the HS group (p = 0.9) and no relationship with clearance (CL) in all study groups. Although we observed an increase in CL for highly PB drugs in ECMO sheep, PB exhibited a weaker negative linear relationship with both CL (HS, p = 0.01; E24H, p < 0.001; SE24H, p < 0.001) and V(ss) (HS, p = 0.01; E24H, p = 0.004; SE24H, p =0.05) in the final model. CONCLUSIONS: Lipophilic antimicrobials are likely to have an increased V(ss) and decreased CL during ECMO. Protein-bound antimicrobial agents are likely to have reductions both in CL and V(ss) during ECMO. The strong relationship between lipophilicity and V(ss) seen in both the E24H and SE24H groups indicates circuit sequestration of lipophilic drugs. These findings highlight the importance of drug factors in predicting antimicrobial drug PK during ECMO and should be a consideration when performing and interpreting population PK studies. BioMed Central 2015-12-15 2015 /pmc/articles/PMC4699331/ /pubmed/26667471 http://dx.doi.org/10.1186/s13054-015-1151-y Text en © Shekar et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Shekar, Kiran
Roberts, Jason A.
Barnett, Adrian G.
Diab, Sara
Wallis, Steven C.
Fung, Yoke L.
Fraser, John F.
Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models
title Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models
title_full Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models
title_fullStr Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models
title_full_unstemmed Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models
title_short Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models
title_sort can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? illustrative data from ovine models
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4699331/
https://www.ncbi.nlm.nih.gov/pubmed/26667471
http://dx.doi.org/10.1186/s13054-015-1151-y
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