Pelligand, L and Lees, P and Sidhu, P K and Toutain, P-L (2019) Semi-Mechanistic Modeling of Florfenicol Time-Kill Curves and in silico Dose Fractionation for Calf Respiratory Pathogens. Frontiers in Microbiology, 10.
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Abstract
An important application of time-kill curve (TKC) assays is determination of the nature of the best PK/PD index (fAUC/MIC or fT% > MIC) and its target value for predicting clinical efficacy in vivo. VetCAST (the veterinary subcommittee of EUCAST) herein presents semi-mechanistic TKC modeling for florfenicol, a long acting (96 h) veterinary antimicrobial drug licensed against calf pneumonia organisms (Pasteurella multocida and Mannheimia haemolytica) to support justification of its PK/PDbreakpoint and clinical breakpoint. Individual TKC assays were performed with 6 field strains of each pathogen (initial inoculum 107 CFU/mL with sampling at times at 0, 1, 2, 4, 8, and 24 h). Semi-mechanistic modeling (Phoenix NLME) allowed precise estimation of bacteria growth system (KGROWTH, natural growth rate; KDEATH, death rate; BMAX, maximum possible culture size) and florfenicol pharmacodynamic parameters (EMAX, efficacy additive to KDEATH; EC50, potency; Gamma, sensitivity). PK/PD simulations (using the present TKC model and parameters of a florfenicol population pharmacokinetic model) predicted the time-course of bacterial counts under different exposures. Of two licensed dosage regimens, 40 mg/kg administered once was predicted to be superior to 20 mg/kg administered at 48 h intervals. Furthermore, we performed in silico dose fractionation with doses 0 – 80 mg/kg administered in 1, 2 or 4 administrations over 96 h and for MICs of 0.5, 1, 2, 4 mg/L with 2 inoculum sizes 105 and 107 CFU/mL. Regression analysis (Imax model) demonstrated that i) fAUC/MIC outperformed fT% > MIC as PK/PD index and ii) maximum efficacy (IC90%) was obtained when the average free plasma concentration over 96 h was equal to 1.2 to 1.4 times the MIC of Pasteurella multocida and Mannheimia haemolytica, respectively.
| Item Type: | Article |
|---|---|
| RVC Publication Type: | Research (full) paper |
| DOI: | https://doi.org/10.3389/fmicb.2019.01237 |
| Departments: | Clinical Sciences and Services Comparative Biomedical Sciences |
| Depositing User: | RVC Auto-import |
| Last Modified: | 20 Nov 2020 22:51 |
| URI: | https://researchonline.rvc.ac.uk/id/eprint/12169 |
| Date Deposited: | 17 June 2019 |
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