Modelling the antimicrobial pharmacodynamics for bacterial strains with versus without acquired resistance to fluoroquinolones or cephalosporins. (March 2022)

• Record Type: Journal Article
• Authors: Salas, Jessica R.; Gaire, Tara; Quichocho, Victoria; Nicholson, Emily; Volkova, Victoriya V.
• Is Part Of: Journal of global antimicrobial resistance. Volume 28(2022)
• Page Start: 59
• Page End: 66
• Publication Date: 2022-03
• Subjects: Pharmacodynamics -- Salmonellae -- Antimicrobials -- Salmonellosis; Drug resistance -- Periodicals; Drug resistance -- Periodicals; Drug resistance; Periodicals; 616.9041
• DOI: 10.1016/j.jgar.2021.10.026
• Languages: English
• ISSNs: 2213-7165

Abstract

Highlights: Predictable changes in antimicrobial pharmacodynamics (PD) against non-typhoidal Salmonellae. PD changes are related to fitness cost for the strains associated with resistance. PD changes may depend on the gene families conferring resistance. ABSTRACT: 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 I max (or E max ) 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.