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Semimechanistic pharmacokinetic/pharmacodynamic model for assessment of activity of antibacterial agents from time-kill curve experiments
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Infectious Diseases.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Infectious Diseases.
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2007 (English)In: Antimicrobial Agents and Chemotherapy, ISSN 0066-4804, E-ISSN 1098-6596, Vol. 51, no 1, 128-136 p.Article in journal (Refereed) Published
Abstract [en]

Dosing of antibacterial agents is generally based on point estimates of the effect, even though bacteria exposed to antibiotics show complex kinetic behaviors. The use of the whole time course of the observed effects would be more advantageous. The aim of the present study was to develop a semimechanistic pharmacokinetic (PK)/pharmacodynamic (PD) model characterizing the events seen in a bacterial system when it is exposed to antibacterial agents with different mechanisms of action. Time-kill curve experiments were performed with a strain of Streptococcus pyogenes exposed to a wide range of concentrations of the following antibiotics: benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, and vancomycin. Bacterial counts were monitored with frequent sampling during the experiment. A simultaneous fit of all data was accomplished. The degradation of the drugs was monitored and corrected for in the model, and a link model was used to account for an effect delay. In the final PK/PD model, the total bacterial population was divided into two subpopulations: one growing drug-susceptible population and one resting insusceptible population. The drug effect was included as an increase of the killing rate of bacteria in the susceptible state, according to a maximum-effect (Emax) model. An internal model validation showed that the model was robust and had good predictability. In conclusion, for all drugs, the final PK/PD model successfully described bacterial growth and killing kinetics when the bacteria were exposed to different antibiotic concentrations. The semimechanistic model that was developed might, after further refinement, serve as a tool for the development of optimal dosing strategies for antibacterial agents.

Place, publisher, year, edition, pages
2007. Vol. 51, no 1, 128-136 p.
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-94169DOI: 10.1128/AAC.00604-06ISI: 000243214200016PubMedID: 17060524OAI: oai:DiVA.org:uu-94169DiVA: diva2:167925
Available from: 2006-03-31 Created: 2006-03-31 Last updated: 2011-05-04Bibliographically approved
In thesis
1. Using Pharmacokinetic and Pharmacodynamic Principles to Evaluate Individualisation of Antibiotic Dosing – Emphasis on Cefuroxime
Open this publication in new window or tab >>Using Pharmacokinetic and Pharmacodynamic Principles to Evaluate Individualisation of Antibiotic Dosing – Emphasis on Cefuroxime
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cefuroxime is a renally eliminated antibiotic used against a variety of different bacterial infections. The pharmacokinetics (PK) for cefuroxime was studied in 97 hospitalized patients using population analysis. To be able to measure cefuroxime in human serum a new sensitive analytical method was developed using mass spectrometry detection. The method was validated and shown to be sensitive and selective. Cystatin C was found to be a better covariate for cefuroxime clearance compared to the traditionally used creatinine clearance (CLcr). This relation might be useful when designing dosing strategies for cefuroxime and other renally eliminated drugs.

The time-courses of the biomarkers C-reactive protein (CRP), serum amyloid A (SAA), interleukin-6 (IL-6) and body temperature were studied for the first 72 hours of cefuroxime treatment and was related to the duration of illness previous treatment with cefuroxime and to time to step-down of treatment. When duration of illness was short, CRP and SAA were showed increasing levels. None of the biomarkers could be used to differentiate between early or late step-down of therapy.

By use of known PK and pharmacodynamic (PD) principles, dosing strategies based on CLcr for cefuroxime were estimated using minimization of a risk function. The risk function was constructed with the aim to expose patients to cefuroxime concentration above minimum inhibitory concentration (MIC) for 50 % of the dosing interval and to minimize the amount of drug administered in excess to reach the aim. Based on evaluation using wild type MIC distributions for Escherichia coli and Streptococcus pneumoniae improved dosing strategies were selected.

In vitro experiments were performed exposing Streptococcus pyogenes to constant concentration of benzylpenicillin, cefuroxime, erythromycin, moxifloxacin or vancomycin. A semi-mechanistic PK/PD model characterizing the time-course of the antibacterial effect was developed using all data simultaneously. Internal validation showed the model being predictive and robust.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2006. 57 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 29
Keyword
Pharmacokinetics/Pharmacotherapy, Cefuroxime, pharmacokinetics, pharmacodynamics, dosing individualisation, NONMEM, Farmakokinetik/Farmakoterapi
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-6639 (URN)91-554-6499-8 (ISBN)
Public defence
2006-04-21, B22, BMC, Uppsala, 09:15
Opponent
Supervisors
Available from: 2006-03-31 Created: 2006-03-31 Last updated: 2011-06-27Bibliographically approved
2. Pharmacometric Models for Antibacterial Agents to Improve Dosing Strategies
Open this publication in new window or tab >>Pharmacometric Models for Antibacterial Agents to Improve Dosing Strategies
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Antibiotics are among the most commonly prescribed drugs. Although the majority of these drugs were developed several decades ago, optimal dosage (dose, dosing interval and treatment duration) have still not been well defined. This thesis focuses on the development and evaluation of pharmacometric models that can be used as tools in the establishment of improved dosing strategies for novel and already clinically available antibacterial drugs.

Infectious diseases are common causes of death in preterm and term newborn infants. A population pharmacokinetic (PK) model for gentamicin was developed based on data from a prospective study. Body-weight and age (gestational and post-natal age) were found to be major factors contributing to variability in gentamicin clearance and therefore important patient characteristics to consider for improved dosing regimens.

A semi-mechanistic pharmacokinetic-pharmacodynamic (PKPD) model was also developed, to characterize in vitro bacterial growth and killing kinetics following exposure to six antibacterial drugs, representing a broad selection of mechanisms of action and PK as well as PD characteristics. The model performed well in describing a wide range of static and dynamic drug exposures and was easily applied to other bacterial strains and antibiotics. It is, therefore, likely to find application in early drug development programs.

Dosing of antibiotics is usually based on summary endpoints such as the PK/PD indices. Predictions based on the PKPD model showed that the commonly used PK/PD indices were well identified for all investigated drugs, supporting that models based on in vitro data can be predictive of antibacterial effects observed in vivo. However, the PK/PD indices were sensitive to the study conditions and were not always consistent between patient populations. The PK/PD indices may therefore extrapolate poorly across sub-populations. A semi-mechanistic modeling approach, utilizing the type of models described here, may thus have higher predictive value in a dose optimization tailored to specific patient populations.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2011. 75 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 138
Keyword
Pharmacometrics, pharmacokinetics, pharmacodynamics, modeling, NONMEM, antibiotics, in vitro, time-kill curve, PK/PD indices, gentamicin, aminoglycosides, newborn infants, premature infants, cystatin C
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
urn:nbn:se:uu:diva-144909 (URN)978-91-554-8002-8 (ISBN)
Public defence
2011-03-25, B41, Biomedicinskt Centrum, Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2011-03-03 Created: 2011-02-03 Last updated: 2011-05-04

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Nielsen, Elisabet I.Löwdin, ElisabethCars, OttoKarlsson, Mats O.

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