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Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus

To explore whether susceptibility testing with antibiotic combinations at pharmacokinetically derived concentration ratios is predictive of the antimicrobial effect, a Staphylococcus aureus strain was exposed to daptomycin and gentamicin alone or in combination in multiple dosing experiments. The su...

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Autores principales: Golikova, Maria V., Strukova, Elena N., Portnoy, Yury A., Zinner, Stephen H., Firsov, Alexander A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7557373/
https://www.ncbi.nlm.nih.gov/pubmed/32854240
http://dx.doi.org/10.3390/antibiotics9090538
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author Golikova, Maria V.
Strukova, Elena N.
Portnoy, Yury A.
Zinner, Stephen H.
Firsov, Alexander A.
author_facet Golikova, Maria V.
Strukova, Elena N.
Portnoy, Yury A.
Zinner, Stephen H.
Firsov, Alexander A.
author_sort Golikova, Maria V.
collection PubMed
description To explore whether susceptibility testing with antibiotic combinations at pharmacokinetically derived concentration ratios is predictive of the antimicrobial effect, a Staphylococcus aureus strain was exposed to daptomycin and gentamicin alone or in combination in multiple dosing experiments. The susceptibility of the S. aureus strain to daptomycin and gentamicin in combination was tested at concentration ratios equal to the ratios of 24 h areas under the concentration–time curve (AUC(24)s) of antibiotics simulated in an in vitro dynamic model in five-day treatments. The MICs of daptomycin and gentamicin decreased in the presence of each other; this led to an increase in the antibiotic AUC(24)/MIC ratios and the antibacterial effects. Effects of single and combined treatments were plotted against the AUC(24)/MIC ratios of daptomycin or gentamicin, and a significant sigmoid relationship was obtained. Similarly, when the effects of single and combined treatments were related to the total exposure of both drugs (the sum of AUC(24)/MIC ratios (∑AUC(24)/MIC)), a significant sigmoid relationship was obtained. These findings suggest that (1) the effects of antibiotic combinations can be predicted by AUC(24)/MICs using MICs of each antibacterial determined at pharmacokinetically derived concentration ratios; (2) ∑AUC(24)/MIC is a reliable predictor of the antibacterial effects of antibiotic combinations.
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spelling pubmed-75573732020-10-20 Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus Golikova, Maria V. Strukova, Elena N. Portnoy, Yury A. Zinner, Stephen H. Firsov, Alexander A. Antibiotics (Basel) Article To explore whether susceptibility testing with antibiotic combinations at pharmacokinetically derived concentration ratios is predictive of the antimicrobial effect, a Staphylococcus aureus strain was exposed to daptomycin and gentamicin alone or in combination in multiple dosing experiments. The susceptibility of the S. aureus strain to daptomycin and gentamicin in combination was tested at concentration ratios equal to the ratios of 24 h areas under the concentration–time curve (AUC(24)s) of antibiotics simulated in an in vitro dynamic model in five-day treatments. The MICs of daptomycin and gentamicin decreased in the presence of each other; this led to an increase in the antibiotic AUC(24)/MIC ratios and the antibacterial effects. Effects of single and combined treatments were plotted against the AUC(24)/MIC ratios of daptomycin or gentamicin, and a significant sigmoid relationship was obtained. Similarly, when the effects of single and combined treatments were related to the total exposure of both drugs (the sum of AUC(24)/MIC ratios (∑AUC(24)/MIC)), a significant sigmoid relationship was obtained. These findings suggest that (1) the effects of antibiotic combinations can be predicted by AUC(24)/MICs using MICs of each antibacterial determined at pharmacokinetically derived concentration ratios; (2) ∑AUC(24)/MIC is a reliable predictor of the antibacterial effects of antibiotic combinations. MDPI 2020-08-25 /pmc/articles/PMC7557373/ /pubmed/32854240 http://dx.doi.org/10.3390/antibiotics9090538 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Golikova, Maria V.
Strukova, Elena N.
Portnoy, Yury A.
Zinner, Stephen H.
Firsov, Alexander A.
Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus
title Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus
title_full Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus
title_fullStr Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus
title_full_unstemmed Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus
title_short Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus
title_sort verification of a novel approach to predicting effects of antibiotic combinations: in vitro dynamic model study with daptomycin and gentamicin against staphylococcus aureus
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7557373/
https://www.ncbi.nlm.nih.gov/pubmed/32854240
http://dx.doi.org/10.3390/antibiotics9090538
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