Pharmacokinetic/pharmacodynamic model-based combination therapy approach to target antibiotic resistant populations emerged from ciprofloxacin exposure.
BACKGROUND
Despite decades of antimicrobial usage, the relationship between antimicrobial drugs and the development of drug resistance has not been fully delineated. This has led to increased frequency of resistance with increased usage of antimicrobials. In recent years, new insights into the mechanisms of antibiotic resistance have been proposed, leading to a re-evaluation of novel pharmacokinetic/pharmacodynamic (PK/PD) models. We have developed a semi-mechanistic PK/PD model to describe drug-bacteria kill curve relationships using the compensatory mutation hypothesis. In addition, we explored the model-based combination therapy approach to combat the resistance population.


METHODS
In vitro kill-curves of E. coli 204 up to 48 h following initial ciprofloxacin (CIP) treatment at 0.0, 0.1, 0.2, 0.5, 1.0, 2.0, 4.0, 8.0, 16.0, 32.0 and 125 times the minimum inhibitory concentration (MIC) totaling 193 data points were obtained with an in vitro system with a simulated CIP half-life of 4 h. The proposed antibiotic resistant mechanism mimics the sequential compensatory mutation hypothesis, in which mutations that acquire drug resistant traits are associated with fitness costs. Subsequent restoration of bacterial fitness is necessary for the population to be clinically relevant. Model parameters were estimated from simultaneous fitting of eleven dose groups using Adapt II software. Standard goodness of fit criteria used to obtain the final model included model convergence, Schwartz Criterion, Akaike Information Criterion, residuals versus predicted concentrations and time, and visual inspection.


CONCLUSIONS
The eleven E. coli kill curves after CIP treatment were well described simultaneously by the compensatory mutation model. The emergence of bacterial population with drug resistance characteristics and bacterial fitness restored appears to dominate shortly following CIP treatment. The model suggests a subsequent dose of a different mechanisms of action should be considered for the emerged resistant population.
Wu
B
B
Department of Pharmaceutics, University of Florida, Gainesville, FL 32610, USA.
Derendorf
H
H
D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000493:pharmacokinetics* / Q000494:pharmacology*; D001419:Bacteria / Q000187:drug effects; D002939:Ciprofloxacin / Q000493:pharmacokinetics* / Q000494:pharmacology*; D004338:Drug Combinations; D004352:Drug Resistance, Microbial; D004926:Escherichia coli / Q000187:drug effects / Q000235:genetics; D008826:Microbial Sensitivity Tests; D015233:Models, Statistical; D009154:Mutation / Q000235:genetics
D000900:Anti-Bacterial Agents; D004338:Drug Combinations; D002939:Ciprofloxacin