PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/249536 |
Resumo: | Objectives The aim of this study was to investigate the effect of daptomycin against methicillin-resistant staphylococci (MRSA and MRSE) bacteremia using computer modeling. Methods A pharmacokinetic/pharmacodynamic (PK/PD) modeling strategy to explain the data from an in vitro dynamic model employing time-kill curves for MRSA and MRSE was proposed. Bacterial killing was followed over time by determining viable counts and the resulting time-kill data was analyzed. Monte Carlo simulations were performed using pharmacokinetic parameters and pharmacodynamic data to determine the probabilities of target attainment and cumulative fractions of response in terms of area under the concentration curve/minimum inhibition concentration (MIC) targets of daptomycin. Simulations were conducted to assess the reduction in the number of colony-forming units (CFU)/mL for 18 days of treatment with daptomycin at doses of 6, 8, and 10 mg/kg/24 h or 48 h with variations in creatinine clearance ( CLCR): 15–29 mL/ min/1.73 m2, 30–49 mL/min/1.73 m2, 50–100 mL/min/1.73 m2, as well as for defining the probability of reaching the target fAUC/MIC = 80 in the same dose and clearance range. A PK/PD model with saturation in the number of bacteria in vitro, growth delay, and bacterial death, as well as Hill’s factor, was used to describe the data for both MRSA and MRSE. Results Monte Carlo simulations showed that for MRSA there was a reduction > 2 log CFU/mL with doses ≥ 6 mg/kg/day in 75th percentile of the simulated population after 18 days of treatment with daptomycin, whereas for MRSE this reduction was observed in 95th percentile of the population. Conclusions The presented in vitro PK/PD model and associated modeling approach were able to characterize the timekill kinetics of MRSA and MRSE. Our study based on PTAs suggests that doses ≥ 6 mg/kg/day of daptomycin should be used to treat bacteremia caused by MRSA and MRSE in patients with CLCR of 15–29 mL/min/1.73 m2. For patients with CLCR ≥ 50 mL/min/1.73 m2, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. |
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Menezes, Bruna KochhannAlves, Izabel AlmeidaStaudt, Keli JaquelineBeltrame, Betina MontanariVenz, LetíciaMichelin, LessandraAraújo, Bibiana Verlindo deTasso, Leandro2022-10-03T04:48:32Z20211517-8382http://hdl.handle.net/10183/249536001149163Objectives The aim of this study was to investigate the effect of daptomycin against methicillin-resistant staphylococci (MRSA and MRSE) bacteremia using computer modeling. Methods A pharmacokinetic/pharmacodynamic (PK/PD) modeling strategy to explain the data from an in vitro dynamic model employing time-kill curves for MRSA and MRSE was proposed. Bacterial killing was followed over time by determining viable counts and the resulting time-kill data was analyzed. Monte Carlo simulations were performed using pharmacokinetic parameters and pharmacodynamic data to determine the probabilities of target attainment and cumulative fractions of response in terms of area under the concentration curve/minimum inhibition concentration (MIC) targets of daptomycin. Simulations were conducted to assess the reduction in the number of colony-forming units (CFU)/mL for 18 days of treatment with daptomycin at doses of 6, 8, and 10 mg/kg/24 h or 48 h with variations in creatinine clearance ( CLCR): 15–29 mL/ min/1.73 m2, 30–49 mL/min/1.73 m2, 50–100 mL/min/1.73 m2, as well as for defining the probability of reaching the target fAUC/MIC = 80 in the same dose and clearance range. A PK/PD model with saturation in the number of bacteria in vitro, growth delay, and bacterial death, as well as Hill’s factor, was used to describe the data for both MRSA and MRSE. Results Monte Carlo simulations showed that for MRSA there was a reduction > 2 log CFU/mL with doses ≥ 6 mg/kg/day in 75th percentile of the simulated population after 18 days of treatment with daptomycin, whereas for MRSE this reduction was observed in 95th percentile of the population. Conclusions The presented in vitro PK/PD model and associated modeling approach were able to characterize the timekill kinetics of MRSA and MRSE. Our study based on PTAs suggests that doses ≥ 6 mg/kg/day of daptomycin should be used to treat bacteremia caused by MRSA and MRSE in patients with CLCR of 15–29 mL/min/1.73 m2. For patients with CLCR ≥ 50 mL/min/1.73 m2, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias.application/pdfengBrazilian journal of microbiology. São Paulo. Vol. 52 (2021), p. 1967–1979AntibacterianosDaptomicinaBacteriemiaBacteremiaDaptomycinPK/PD modelingMonte Carlo simulationPK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatmentinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001149163.pdf.txt001149163.pdf.txtExtracted Texttext/plain43736http://www.lume.ufrgs.br/bitstream/10183/249536/2/001149163.pdf.txt27811c11d6aee19703a343266c09af76MD52ORIGINAL001149163.pdfTexto completo (inglês)application/pdf2291897http://www.lume.ufrgs.br/bitstream/10183/249536/1/001149163.pdf982bea6688772aea68d84b31fb96e0d5MD5110183/2495362022-10-04 05:01:02.504oai:www.lume.ufrgs.br:10183/249536Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2022-10-04T08:01:02Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
title |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
spellingShingle |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment Menezes, Bruna Kochhann Antibacterianos Daptomicina Bacteriemia Bacteremia Daptomycin PK/PD modeling Monte Carlo simulation |
title_short |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
title_full |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
title_fullStr |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
title_full_unstemmed |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
title_sort |
PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
author |
Menezes, Bruna Kochhann |
author_facet |
Menezes, Bruna Kochhann Alves, Izabel Almeida Staudt, Keli Jaqueline Beltrame, Betina Montanari Venz, Letícia Michelin, Lessandra Araújo, Bibiana Verlindo de Tasso, Leandro |
author_role |
author |
author2 |
Alves, Izabel Almeida Staudt, Keli Jaqueline Beltrame, Betina Montanari Venz, Letícia Michelin, Lessandra Araújo, Bibiana Verlindo de Tasso, Leandro |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Menezes, Bruna Kochhann Alves, Izabel Almeida Staudt, Keli Jaqueline Beltrame, Betina Montanari Venz, Letícia Michelin, Lessandra Araújo, Bibiana Verlindo de Tasso, Leandro |
dc.subject.por.fl_str_mv |
Antibacterianos Daptomicina Bacteriemia |
topic |
Antibacterianos Daptomicina Bacteriemia Bacteremia Daptomycin PK/PD modeling Monte Carlo simulation |
dc.subject.eng.fl_str_mv |
Bacteremia Daptomycin PK/PD modeling Monte Carlo simulation |
description |
Objectives The aim of this study was to investigate the effect of daptomycin against methicillin-resistant staphylococci (MRSA and MRSE) bacteremia using computer modeling. Methods A pharmacokinetic/pharmacodynamic (PK/PD) modeling strategy to explain the data from an in vitro dynamic model employing time-kill curves for MRSA and MRSE was proposed. Bacterial killing was followed over time by determining viable counts and the resulting time-kill data was analyzed. Monte Carlo simulations were performed using pharmacokinetic parameters and pharmacodynamic data to determine the probabilities of target attainment and cumulative fractions of response in terms of area under the concentration curve/minimum inhibition concentration (MIC) targets of daptomycin. Simulations were conducted to assess the reduction in the number of colony-forming units (CFU)/mL for 18 days of treatment with daptomycin at doses of 6, 8, and 10 mg/kg/24 h or 48 h with variations in creatinine clearance ( CLCR): 15–29 mL/ min/1.73 m2, 30–49 mL/min/1.73 m2, 50–100 mL/min/1.73 m2, as well as for defining the probability of reaching the target fAUC/MIC = 80 in the same dose and clearance range. A PK/PD model with saturation in the number of bacteria in vitro, growth delay, and bacterial death, as well as Hill’s factor, was used to describe the data for both MRSA and MRSE. Results Monte Carlo simulations showed that for MRSA there was a reduction > 2 log CFU/mL with doses ≥ 6 mg/kg/day in 75th percentile of the simulated population after 18 days of treatment with daptomycin, whereas for MRSE this reduction was observed in 95th percentile of the population. Conclusions The presented in vitro PK/PD model and associated modeling approach were able to characterize the timekill kinetics of MRSA and MRSE. Our study based on PTAs suggests that doses ≥ 6 mg/kg/day of daptomycin should be used to treat bacteremia caused by MRSA and MRSE in patients with CLCR of 15–29 mL/min/1.73 m2. For patients with CLCR ≥ 50 mL/min/1.73 m2, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021 |
dc.date.accessioned.fl_str_mv |
2022-10-03T04:48:32Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/other |
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info:eu-repo/semantics/publishedVersion |
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http://hdl.handle.net/10183/249536 |
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1517-8382 |
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001149163 |
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http://hdl.handle.net/10183/249536 |
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Brazilian journal of microbiology. São Paulo. Vol. 52 (2021), p. 1967–1979 |
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