Modelling the antimicrobial pharmacodynamics for bacterial strains with versus without acquired resistance to fluoroquinolones or cephalosporins.

OBJECTIVES: Antimicrobial resistance threatens therapeutic options for human and animal bacterial diseases worldwide. Current antimicrobial treatment regimens were designed against bacterial strains that were fully susceptible to them. To expand the useable lifetime of existing antimicrobial drug classes by modifying treatment regimens, data are needed on the antimicrobial pharmacodynamics (PD) against strains with reduced susceptibility. In this study, we generated and mathematically modelled the PD of the fluoroquinolone ciprofloxacin and the cephalosporin ceftriaxone against non-typhoidal Salmonella enterica subsp. enterica strains with varying levels of acquired resistance. METHODS: We included Salmonella strains across categories of reduced susceptibility to fluoroquinolones or cephalosporins reported to date, including isolates from human infections, food-animal products sold in retail, and food-animal production. We generated PD data for each drug and strain via time-kill assay. Mathematical models were compared in their fit to represent the PD. The best-fit model's parameter values across the strain susceptibility categories were compared. RESULTS: The inhibitory baseline sigmoid Imax (or Emax) model was best fit for the PD of each antimicrobial against a majority of the strains. There were statistically significant differences in the PD parameter values across the strain susceptibility categories for each antimicrobial. CONCLUSION: The results demonstrate predictable multiparameter changes in the PD of these first-line antimicrobials depending on the Salmonella strain's susceptibility phenotype and specific genes conferring reduced susceptibility. The generated PD parameter estimates could be used to optimise treatment regimens against infections by strains with reduced susceptibility.

Variation in fluoroquinolone pharmacodynamic parameter values among isolates of two bacterial pathogens of bovine respiratory disease.

To design an antimicrobial treatment regimen for a bacterial disease, data on the drug pharmacodynamics (PD) against selected drug-susceptible strains of the pathogen are used. The regimen is applied across such strains in the field, assuming the PD parameter values remain the same. We used time-kill experiments and PD modeling to investigate the fluoroquinolone enrofloxacin PD against different isolates of two bovine respiratory disease pathogens: four Mannheimia haemolytica and three Pasteurella multocida isolates. The models were fitted as mixed-effects non-linear regression; the fixed-effects PD parameter values were estimated after accounting for random variation among experimental replicates. There was both inter- and intra- bacterial species variability in the PD parameters Hill-coefficient and Emax (maximal decline of bacterial growth rate), with more variable PD responses among M. haemolytica than among P. multocida isolates. Moreover, the Hill-coefficient was correlated to the isolate's maximal population growth rate in the absence of antimicrobial exposure (a.k.a. specific growth rate; Spearman's ρ = 0.98, p-value = 0.003, n = 6 isolates excluding one outlier). Thus, the strain's properties such as growth potential may impact its PD responses. This variability can have clinical implications. Modifying the treatment regimen depending on phenotypic properties of the pathogen strain causing disease may be a precision medicine approach.