PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment
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 employin...
Ausführliche Beschreibung
Autor*in: |
Menezes, Bruna [verfasserIn] Alves, Izabel [verfasserIn] Staudt, Keli [verfasserIn] Beltrame, Betina [verfasserIn] Michelin, Lessandra [verfasserIn] de Araújo, Bibiana Verlindo [verfasserIn] Tasso, Leandro [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2021 |
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Schlagwörter: |
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Anmerkung: |
© Sociedade Brasileira de Microbiologia 2021 |
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Übergeordnetes Werk: |
Enthalten in: Brazilian journal of microbiology - [Cham] : Springer International Publishing, 2000, 52(2021), 4 vom: 02. Aug., Seite 1967-1979 |
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Übergeordnetes Werk: |
volume:52 ; year:2021 ; number:4 ; day:02 ; month:08 ; pages:1967-1979 |
Links: |
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DOI / URN: |
10.1007/s42770-021-00582-4 |
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Katalog-ID: |
SPR045525293 |
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245 | 1 | 0 | |a PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
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520 | |a 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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. | ||
650 | 4 | |a Bacteremia |7 (dpeaa)DE-He213 | |
650 | 4 | |a Daptomycin |7 (dpeaa)DE-He213 | |
650 | 4 | |a PK/PD modeling |7 (dpeaa)DE-He213 | |
650 | 4 | |a Monte Carlo simulation |7 (dpeaa)DE-He213 | |
700 | 1 | |a Alves, Izabel |e verfasserin |4 aut | |
700 | 1 | |a Staudt, Keli |e verfasserin |4 aut | |
700 | 1 | |a Beltrame, Betina |e verfasserin |4 aut | |
700 | 1 | |a Michelin, Lessandra |e verfasserin |4 aut | |
700 | 1 | |a de Araújo, Bibiana Verlindo |e verfasserin |4 aut | |
700 | 1 | |a Tasso, Leandro |e verfasserin |4 aut | |
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10.1007/s42770-021-00582-4 doi (DE-627)SPR045525293 (SPR)s42770-021-00582-4-e DE-627 ger DE-627 rakwb eng 570 ASE 570 ASE 42.00 bkl Menezes, Bruna verfasserin aut PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sociedade Brasileira de Microbiologia 2021 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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. Bacteremia (dpeaa)DE-He213 Daptomycin (dpeaa)DE-He213 PK/PD modeling (dpeaa)DE-He213 Monte Carlo simulation (dpeaa)DE-He213 Alves, Izabel verfasserin aut Staudt, Keli verfasserin aut Beltrame, Betina verfasserin aut Michelin, Lessandra verfasserin aut de Araújo, Bibiana Verlindo verfasserin aut Tasso, Leandro verfasserin aut Enthalten in Brazilian journal of microbiology [Cham] : Springer International Publishing, 2000 52(2021), 4 vom: 02. Aug., Seite 1967-1979 (DE-627)320577465 (DE-600)2017175-4 1678-4405 nnns volume:52 year:2021 number:4 day:02 month:08 pages:1967-1979 https://dx.doi.org/10.1007/s42770-021-00582-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 52 2021 4 02 08 1967-1979 |
spelling |
10.1007/s42770-021-00582-4 doi (DE-627)SPR045525293 (SPR)s42770-021-00582-4-e DE-627 ger DE-627 rakwb eng 570 ASE 570 ASE 42.00 bkl Menezes, Bruna verfasserin aut PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sociedade Brasileira de Microbiologia 2021 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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. Bacteremia (dpeaa)DE-He213 Daptomycin (dpeaa)DE-He213 PK/PD modeling (dpeaa)DE-He213 Monte Carlo simulation (dpeaa)DE-He213 Alves, Izabel verfasserin aut Staudt, Keli verfasserin aut Beltrame, Betina verfasserin aut Michelin, Lessandra verfasserin aut de Araújo, Bibiana Verlindo verfasserin aut Tasso, Leandro verfasserin aut Enthalten in Brazilian journal of microbiology [Cham] : Springer International Publishing, 2000 52(2021), 4 vom: 02. Aug., Seite 1967-1979 (DE-627)320577465 (DE-600)2017175-4 1678-4405 nnns volume:52 year:2021 number:4 day:02 month:08 pages:1967-1979 https://dx.doi.org/10.1007/s42770-021-00582-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 52 2021 4 02 08 1967-1979 |
allfields_unstemmed |
10.1007/s42770-021-00582-4 doi (DE-627)SPR045525293 (SPR)s42770-021-00582-4-e DE-627 ger DE-627 rakwb eng 570 ASE 570 ASE 42.00 bkl Menezes, Bruna verfasserin aut PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sociedade Brasileira de Microbiologia 2021 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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. Bacteremia (dpeaa)DE-He213 Daptomycin (dpeaa)DE-He213 PK/PD modeling (dpeaa)DE-He213 Monte Carlo simulation (dpeaa)DE-He213 Alves, Izabel verfasserin aut Staudt, Keli verfasserin aut Beltrame, Betina verfasserin aut Michelin, Lessandra verfasserin aut de Araújo, Bibiana Verlindo verfasserin aut Tasso, Leandro verfasserin aut Enthalten in Brazilian journal of microbiology [Cham] : Springer International Publishing, 2000 52(2021), 4 vom: 02. Aug., Seite 1967-1979 (DE-627)320577465 (DE-600)2017175-4 1678-4405 nnns volume:52 year:2021 number:4 day:02 month:08 pages:1967-1979 https://dx.doi.org/10.1007/s42770-021-00582-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 52 2021 4 02 08 1967-1979 |
allfieldsGer |
10.1007/s42770-021-00582-4 doi (DE-627)SPR045525293 (SPR)s42770-021-00582-4-e DE-627 ger DE-627 rakwb eng 570 ASE 570 ASE 42.00 bkl Menezes, Bruna verfasserin aut PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sociedade Brasileira de Microbiologia 2021 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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. Bacteremia (dpeaa)DE-He213 Daptomycin (dpeaa)DE-He213 PK/PD modeling (dpeaa)DE-He213 Monte Carlo simulation (dpeaa)DE-He213 Alves, Izabel verfasserin aut Staudt, Keli verfasserin aut Beltrame, Betina verfasserin aut Michelin, Lessandra verfasserin aut de Araújo, Bibiana Verlindo verfasserin aut Tasso, Leandro verfasserin aut Enthalten in Brazilian journal of microbiology [Cham] : Springer International Publishing, 2000 52(2021), 4 vom: 02. Aug., Seite 1967-1979 (DE-627)320577465 (DE-600)2017175-4 1678-4405 nnns volume:52 year:2021 number:4 day:02 month:08 pages:1967-1979 https://dx.doi.org/10.1007/s42770-021-00582-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 52 2021 4 02 08 1967-1979 |
allfieldsSound |
10.1007/s42770-021-00582-4 doi (DE-627)SPR045525293 (SPR)s42770-021-00582-4-e DE-627 ger DE-627 rakwb eng 570 ASE 570 ASE 42.00 bkl Menezes, Bruna verfasserin aut PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sociedade Brasileira de Microbiologia 2021 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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. Bacteremia (dpeaa)DE-He213 Daptomycin (dpeaa)DE-He213 PK/PD modeling (dpeaa)DE-He213 Monte Carlo simulation (dpeaa)DE-He213 Alves, Izabel verfasserin aut Staudt, Keli verfasserin aut Beltrame, Betina verfasserin aut Michelin, Lessandra verfasserin aut de Araújo, Bibiana Verlindo verfasserin aut Tasso, Leandro verfasserin aut Enthalten in Brazilian journal of microbiology [Cham] : Springer International Publishing, 2000 52(2021), 4 vom: 02. Aug., Seite 1967-1979 (DE-627)320577465 (DE-600)2017175-4 1678-4405 nnns volume:52 year:2021 number:4 day:02 month:08 pages:1967-1979 https://dx.doi.org/10.1007/s42770-021-00582-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 52 2021 4 02 08 1967-1979 |
language |
English |
source |
Enthalten in Brazilian journal of microbiology 52(2021), 4 vom: 02. Aug., Seite 1967-1979 volume:52 year:2021 number:4 day:02 month:08 pages:1967-1979 |
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Enthalten in Brazilian journal of microbiology 52(2021), 4 vom: 02. Aug., Seite 1967-1979 volume:52 year:2021 number:4 day:02 month:08 pages:1967-1979 |
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Bacteremia Daptomycin PK/PD modeling Monte Carlo simulation |
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Brazilian journal of microbiology |
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Menezes, Bruna @@aut@@ Alves, Izabel @@aut@@ Staudt, Keli @@aut@@ Beltrame, Betina @@aut@@ Michelin, Lessandra @@aut@@ de Araújo, Bibiana Verlindo @@aut@@ Tasso, Leandro @@aut@@ |
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2021-08-02T00:00:00Z |
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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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. 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Menezes, Bruna |
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Menezes, Bruna ddc 570 bkl 42.00 misc Bacteremia misc Daptomycin misc PK/PD modeling misc Monte Carlo simulation PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
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570 ASE 42.00 bkl PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment Bacteremia (dpeaa)DE-He213 Daptomycin (dpeaa)DE-He213 PK/PD modeling (dpeaa)DE-He213 Monte Carlo simulation (dpeaa)DE-He213 |
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ddc 570 bkl 42.00 misc Bacteremia misc Daptomycin misc PK/PD modeling misc Monte Carlo simulation |
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ddc 570 bkl 42.00 misc Bacteremia misc Daptomycin misc PK/PD modeling misc Monte Carlo simulation |
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PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
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PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
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Menezes, Bruna |
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Menezes, Bruna Alves, Izabel Staudt, Keli Beltrame, Betina Michelin, Lessandra de Araújo, Bibiana Verlindo Tasso, Leandro |
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pk/pd modeling of daptomycin against mrsa and mrse and monte carlo simulation for bacteremia treatment |
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PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
abstract |
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 ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. © Sociedade Brasileira de Microbiologia 2021 |
abstractGer |
Objectives The aim of this study was to investigate the effect of daptomycin against methicillin-resistant staphylococci (MRSA and MRSE) bacteremia using computer modeling. Methods A pharmacokinetic/pharmacodynamic (PK/PD) modeling strategy to explain the data from an in vitro dynamic model employing time-kill curves for MRSA and MRSE was proposed. Bacterial killing was followed over time by determining viable counts and the resulting time-kill data was analyzed. Monte Carlo simulations were performed using pharmacokinetic parameters and pharmacodynamic data to determine the probabilities of target attainment and cumulative fractions of response in terms of area under the concentration curve/minimum inhibition concentration (MIC) targets of daptomycin. Simulations were conducted to assess the reduction in the number of colony-forming units (CFU)/mL for 18 days of treatment with daptomycin at doses of 6, 8, and 10 mg/kg/24 h or 48 h with variations in creatinine clearance ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. © Sociedade Brasileira de Microbiologia 2021 |
abstract_unstemmed |
Objectives The aim of this study was to investigate the effect of daptomycin against methicillin-resistant staphylococci (MRSA and MRSE) bacteremia using computer modeling. Methods A pharmacokinetic/pharmacodynamic (PK/PD) modeling strategy to explain the data from an in vitro dynamic model employing time-kill curves for MRSA and MRSE was proposed. Bacterial killing was followed over time by determining viable counts and the resulting time-kill data was analyzed. Monte Carlo simulations were performed using pharmacokinetic parameters and pharmacodynamic data to determine the probabilities of target attainment and cumulative fractions of response in terms of area under the concentration curve/minimum inhibition concentration (MIC) targets of daptomycin. Simulations were conducted to assess the reduction in the number of colony-forming units (CFU)/mL for 18 days of treatment with daptomycin at doses of 6, 8, and 10 mg/kg/24 h or 48 h with variations in creatinine clearance ($ CL_{CR} $): 15–29 mL/min/1.73 $ m^{2} $, 30–49 mL/min/1.73 $ m^{2} $, 50–100 mL/min/1.73 $ m^{2} $, 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 time-kill 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 $ CL_{CR} $ of 15–29 mL/min/1.73 $ m^{2} $. For patients with $ CL_{CR} $ ≥ 50 mL/min/1.73 $ m^{2} $, it would be necessary to employ a dose of 10 mg/kg/day to treat complicated bacteremias. © Sociedade Brasileira de Microbiologia 2021 |
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PK/PD modeling of daptomycin against MRSA and MRSE and Monte Carlo simulation for bacteremia treatment |
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https://dx.doi.org/10.1007/s42770-021-00582-4 |
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score |
7.4006453 |