Abstract
BackgroundIn order to provide some basis for effective dosage regimens that optimize efficacy with respect to bacteriological and clinical cures, the in vivo activity of cefquinome against a clinical Escherichia coli (E.coli) strain (the minimum inhibitory concentration value for this strain equals to the MIC90 value of 0.25 μg/ml for 210 E.coli strains isolated from pigs) was investigated by using a piglet tissue-cage infection model. The aim was to elucidate the pharmacokinetic/pharmacodynamics (PK/PD) index associated with cefquinome efficacy, and then to identify the magnitude of the PK/PD parameter required for different degree of efficacy in clinical treatment.ResultsTissue-cage infection model was established in piglets, and then the animals received intramuscular injection of cefquinome twice a day for 3 days to create a range of different drug exposures. The tissue-cage fluid was collected at 1, 3, 6, 9 and 12 h after every drug administration for drug concentration determination and bacteria counting. Different cefquinome regimens produced different percentages of time during that drug concentrations exceeded the MIC (%T > MIC), ranging from 0 % to 100 %. Cefquinome administration at 0.2, 0.4, 0.6, 0.8, 1, 2 and 4 mg/kg reduced the bacterial count (log10 CFU/mL) in tissue-cage fluid by −1.00 ± 0.32, −1.83 ± 0.08, −2.33 ± 0.04, −2.96 ± 0.16, −2.99 ± 0.16, −2.93 ± 0.11, −3.43 ± 0.18, respectively. The correlation coefficient of the PK/PD index with antibacterial effect of the drug was 0.90 for %T > MIC, 0.62 for AUC0–12/MIC, and 0.61 for Cmax/MIC, suggesting the most important PK/PD parameter was %T > MIC. A inhibitory form of sigmoid maximum effect (Emax) model was used to estimate %T > MIC, and the respective values required for continuous 1/6-log drop, 1/3-log drop and 1/2-log drop of the clinical E.coli count during each 12 h treatment period were 3.97 %, 17.08 % and 52.68 %.ConclusionsThe data derived from this study showed that cefquinome exhibited time-dependent killing profile. And from the results of the present study, it can be assumed that when %T > MIC reached 52.68 %, cefquinome could be expected to be effective against a clinical E.coli strain for which the MIC value is below 0.128 μg/ml (3-log drop of bacteria count can be achieved after six successive administrations for 3 days).
Highlights
In order to provide some basis for effective dosage regimens that optimize efficacy with respect to bacteriological and clinical cures, the in vivo activity of cefquinome against a clinical Escherichia coli (E.coli) strain was investigated by using a piglet tissue-cage infection model
The difference of the bacterial count in the control sample; E0, the maximum antibacterial effect during 12 h treatment period; N, the Hill coefficient that describes the steepness of the effect curve. %T > minimum inhibitory concentration (MIC), the values of cefquinome required to achieve 1/6-log drop, 1/3-log drop and 1/2-log drop against the clinical E.coli strain during 12 h treatment period aureus, Streptococcus pneumoniae, and Enterococcus faecalis [21], and piperacillin against E.coli [22], cefquinome against Staphylococcus aureus [23]
The current study characterized the in vivo response of a clinical E.coli strain to cefquinome in a piglet tissue-cage infection model after different dosing
Summary
In order to provide some basis for effective dosage regimens that optimize efficacy with respect to bacteriological and clinical cures, the in vivo activity of cefquinome against a clinical Escherichia coli (E.coli) strain (the minimum inhibitory concentration value for this strain equals to the MIC90 value of 0.25 μg/ml for 210 E.coli strains isolated from pigs) was investigated by using a piglet tissue-cage infection model. Among the documented misuses contributing to drug resistance are inappropriate dosage regimens (dose, dosage interval, duration of treatment, route and conditions of administration) (Anonymous 1998). Rational antibiotic therapy requires dosage regimens to be optimized, to guarantee clinical efficacy, and to minimize the selection and spread of resistant pathogens [1]. Jacobs thought pharmacokinetics (PK) and pharmacodynamics (PD) should be considered to establish optimal dosing regimens for antimicrobials [2]. Toutain and Lees thought that the parameters derived from PK/ PD modelling may be used as an alternative and preferred approach to dose titration studies for selecting rational dosage regimens (both dose and dosing interval) for further evaluation in clinical trials [3]
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