Model-informed drug development for antimicrobials: translational pharmacokinetic-pharmacodynamic modelling of apramycin to facilitate prediction of efficacious dose in complicated urinary tract infections.

Objectives: The use of mouse models of complicated urinary tract infection (cUTI) has usually been limited to a single timepoint assessment of bacterial burden. Based on longitudinal in vitro and in vivo data, we developed a pharmacokinetic-pharmacodynamic (PKPD) model to assess the efficacy of apramycin, a broad-spectrum aminoglycoside antibiotic, in mouse models of cUTI.

Methods: Two Escherichia coli strains were studied (EN591 and ATCC 700336). Apramycin exposure-effect relationships were established with in vitro time-kill data at pH 6 and pH 7.4 and in mice with cUTI. Immunocompetent mice were treated with apramycin (1.5-30 mg/kg) starting 24 h post-infection. Kidney and bladder tissue were collected 6-96 h post-infection for cfu determination. A PKPD model integrating all data was developed and simulations were performed to predict bacterial burden in humans.

Results: Treatment with apramycin reduced the bacterial load in kidneys and bladder tissue up to 4.3-log compared with vehicle control. In vitro and in vivo tissue time-course efficacy data were integrated into the PKPD model, showing 76%-98% reduction of bacterial net growth and 3- to 145-fold increase in apramycin potency in vivo compared with in vitro. Simulations suggested that an 11 mg/kg daily dose would be sufficient to achieve bacterial stasis in kidneys and bladder in humans.

Conclusions: PKPD modelling with in vitro and in vivo PK and PD data enabled simultaneous evaluation of the different components that influence drug effect, an approach that had not yet been evaluated for antibiotics in the cUTI model and that has potential to enhance model-informed drug development of antibiotics.