Pharmacokinetics and pharmacodynamics of enrofloxacin treatment of Escherichia coli in a murine thigh infection modeling

Abstract

Abstract Background Enrofloxacin is an antibacterial drug with broad-spectrum activity that is widely indicated for veterinary use. We aim to develop the clinical applications of Enrofloxacin against colibacillosis by using the neutropenic mice thigh infection model. Results The minimum inhibitory concentration (MIC) distribution of 67 isolated E. coli strains to ENR was calculated using CLSI guidelines. Whereas, the MIC50 value calculation was considered as the population PD parameter for ENR against E. coli strains. The MIC values of 15 E. coli strains were found to be nearest to the MIC50 i.e., 0.25 μg/mL. Of all the tested strains, the PK-PD and E. coli disease model was established via selected E. coli strain i.e., Heilong 15. We analyzed the PK characteristics of ENR and its metabolite ciprofloxacin (CIP) following a single subcutaneous (s.c.) injection of ENR (1.25, 2.5, 5, 10 mg/kg). The concentration-time profiling of ENR within the plasma specimens was determined by considering the non-compartmental analysis (NCA). The basic PK parameters of ENR for the peak drug concentration (Cmax) and the area under the concentration-time curve (AUC) values were found to be in the range of 0.27–1.97 μg/mL and 0.62–3.14 μg.h/mL, respectively. Multiple s.c. injection over 24 h (1.25, 2.5, 5, 10 mg/kg at various time points i.e., 6, 8, 12, and 24 h respectively) were administered to assess the targeted PD values. The Akaike Information Criterion (AIC) was used to choose PD models, and the model with the lowest AIC was chosen. The inhibitory Emax model was employed to calculate the related PK-PD parameters. The results of our study indicated that there was a strong correlation between the AUC/MIC and various antibacterial activities (R2 = 0.9928). The target values of dividing AUC/MIC by 24 h for bacteriostatic action were 1-log10 reduction, 2-log10 reduction, and 3-log10 reduction 0.325, 0.4375, 0.63, and 0.95 accordingly. Conclusion The identified pharmacodynamics targets for various antibacterial effects will be crucial in enhancing ENR clinical applications and serving as a key step in reducing bacterial resistance.