Pharmacokinetic-Pharmacodynamic Model for Gentamicin and Its Adaptive Resistance with Predictions of Dosing Schedules in Newborn Infants

Mohamed, Ami Fazlin Syed; Nielsen, Elisabet I.; Cars, Otto; Friberg, Lena E.

doi:10.1128/aac.00694-11

Cited by 77 publications

(96 citation statements)

References 41 publications

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“…Potential adaptive resistance (AR) of the bacteria leading to regrowth after initial killing was implemented by an adaption submodel 13, 14. The degree of adaption was assumed to increase EC 50 over time as a function of drug exposure c(t) and a second‐order time‐delay rate constant τ:

\frac{d {A R}_{o f f}}{d t} = - τ \times c true(t true) \times {A R}_{o f f} IC = 1

\frac{d {A R}_{o n}}{d t} = τ \times c true(t true) \times {A R}_{o f f} IC = 0

…”

Section: Methodsmentioning

confidence: 99%

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Wicha

Huisinga

Kloft

2017

CPT Pharmacometrics Syst. Pharmacol.

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Broad‐spectrum antibiotic combination therapy is frequently applied due to increasing resistance development of infective pathogens. The objective of the present study was to evaluate two common empiric broad‐spectrum combination therapies consisting of either linezolid (LZD) or vancomycin (VAN) combined with meropenem (MER) against Staphylococcus aureus (S. aureus) as the most frequent causative pathogen of severe infections. A semimechanistic pharmacokinetic‐pharmacodynamic (PK‐PD) model mimicking a simplified bacterial life‐cycle of S. aureus was developed upon time‐kill curve data to describe the effects of LZD, VAN, and MER alone and in dual combinations. The PK‐PD model was successfully (i) evaluated with external data from two clinical S. aureus isolates and further drug combinations and (ii) challenged to predict common clinical PK‐PD indices and breakpoints. Finally, clinical trial simulations were performed that revealed that the combination of VAN‐MER might be favorable over LZD‐MER due to an unfavorable antagonistic interaction between LZD and MER.

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\frac{d {A R}_{o f f}}{d t} = - τ \times c true(t true) \times {A R}_{o f f} IC = 1

\frac{d {A R}_{o n}}{d t} = τ \times c true(t true) \times {A R}_{o f f} IC = 0

…”

Section: Methodsmentioning

confidence: 99%

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Wicha

Huisinga

Kloft

2017

CPT Pharmacometrics Syst. Pharmacol.

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“…In this report, we have employed a dynamic in vitro PK/PD model and mathematical modeling to explore the effects of differences in concentration-time profiles on the activity of polymyxins and the development of polymyxin resistance due to amplification of preexisting resistant mutants and adaptive resistance (42,43). The developed mathematical model implemented a new observation model that linked adaptive resistance to colony formation on drug-containing plates, extending the utility of previous models of adaptive resistance (31,44).…”

Section: Discussionmentioning

confidence: 99%

Colistin and Polymyxin B Dosage Regimens against Acinetobacter baumannii: Differences in Activity and the Emergence of Resistance

Cheah

Tsuji

et al. 2016

Antimicrob Agents Chemother

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dInfections caused by multidrug-resistant Acinetobacter baumannii are a major public health problem, and polymyxins are often the last line of therapy for recalcitrant infections by such isolates. The pharmacokinetics of the two clinically used polymyxins, polymyxin B and colistin, differ considerably, since colistin is administered as an inactive prodrug that undergoes slow conversion to colistin. However, the impact of these substantial pharmacokinetic differences on bacterial killing and resistance emergence is poorly understood. We assessed clinically relevant polymyxin B and colistin dosage regimens against one reference and three clinical A. baumannii strains in a dynamic one-compartment in vitro model. A new mechanism-based pharmacodynamic model was developed to describe and predict the drug concentrations and viable counts of the total and resistant populations. Rapid attainment of target concentrations was shown to be critical for polymyxin-induced bacterial killing. All polymyxin B regimens achieved peak concentrations of at least 1 mg/liter within 1 h and caused >4 log 10 killing at 1 h. In contrast, the slow rise of colistin concentrations to 3 mg/liter over 48 h resulted in markedly reduced bacterial killing. A significant (4 to 6 log 10 CFU/ ml) amplification of resistant bacterial populations was common to all dosage regimens. The developed mechanism-based model explained the observed bacterial killing, regrowth, and resistance. The model also implicated adaptive polymyxin resistance as a key driver of bacterial regrowth and predicted the amplification of preexisting, highly polymyxin-resistant bacterial populations following polymyxin treatment. Antibiotic combination therapies seem the most promising option for minimizing the emergence of polymyxin resistance.

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“…Our calculations extend two papers (8,9) on PK/PD modeling of neonatal gentamicin treatments. Figure 2 is a condensed summary.…”

Section: Deterministic and Stochastic Neonatal Gentamicin Pk/pd Modelingmentioning

confidence: 48%

“…One PK/PD approach to modeling gentamicin treatment of E. coli in neonates is given in (8,9). The approach takes into account drug-induced "adaptive resistance," which is reversible within days [reviewed in (4,10)]; it does not consider irreversible resistance caused, e.g., by bacterial mutations (11,12).…”

Section: Pk/pd Modelingmentioning

confidence: 99%

Stochastic Process Pharmacodynamics: Dose Timing in Neonatal Gentamicin Therapy as an Example

Radivoyevitch

Siranart

Hlatky

et al. 2015

AAPS J

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ABSTRACT. We consider dosing regimens designed to cure patients by eradicating colony forming units (CFU) such as bacteria. In the field of "population" pharmaco-kinetics/dynamics (PK/PD), interindividual variability (IIV) of patients is estimated using model parameter statistical distributions. We consider a more probabilistic approach to IIV called stochastic process theory, motivated by the fact that tumor treatment planning uses both approaches. Stochastic process PD can supply additional insights and suggest different dosing regimens due to its emphasis on the probability of complete CFU eradication and its predictions on "pure chance" fluctuations of CFU number per patient when treatment has reduced this integer to less than~100. To exemplify the contrast between stochastic process PD models and standard deterministic PD models, which track only average CFU number, we analyze, neglecting immune responses, neonatal intravenous gentamicin dosing regimens directed against Escherichia coli. Our stochastic calculations predict that the first dose is crucial for CFU eradication. For example, a single 6 mg/kg dose is predicted to have a higher eradication probability than four daily 4 mg/kg doses. We conclude: (1) neonatal gentamicin dosing regimens with larger first doses but smaller total doses deserve investigation; (2) in general, if standard PK/PD models predict average CFU number drops substantially below 100, the models should be modified to incorporate stochastic effects more accurately, and will then usually make more favorable, or less unfavorable, predictions for front boosting ("hit hard early"). Various caveats against over-interpreting the calculations are given.

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Pharmacokinetic-Pharmacodynamic Model for Gentamicin and Its Adaptive Resistance with Predictions of Dosing Schedules in Newborn Infants

Cited by 77 publications

References 41 publications

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Colistin and Polymyxin B Dosage Regimens against Acinetobacter baumannii: Differences in Activity and the Emergence of Resistance

Stochastic Process Pharmacodynamics: Dose Timing in Neonatal Gentamicin Therapy as an Example

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