Optimisation of antibiotic therapy for resistant infections

Author: Dr Fekade Sime, Research Fellow, UQ School of Pharmacy. 

The University of Queensland’s Centre for Translational Anti-infective Pharmacodynamics (CTAP) is leading the fight against antibiotic-resistant superbugs through its research into optimising antibiotic therapy for these resistant infections.

In the critical care setting, it is not uncommon to see complicated infections that were initially responsive to treatment become resistant to antibiotics during the course of therapy and result in patient death.

This partly relates to inadequacy of conventional dosing regimens to ensure maximal bacterial killing in severely ill patient populations.

Moreover, these conventional doses are only validated for the treatment of infections caused by quite susceptible pathogens, and clinicians have little information on how to optimise antibiotic doses when they face less susceptible or resistant bugs.

Consequently, clinicians resort to an empiric approach to therapy which risks worsening of the problem of resistance.

It is highly important that novel dosing regimens that suppress emergence of resistance and maximise bacterial killing in less susceptible, resistant infections are urgently developed.

The newly established CTAP will use state-of-the-art, dynamic in vitro infection models to assess the adequacy of conventional dosing regimens for suppression of emergence of resistance, and also describe optimal antibiotic dosing regimens that maximise bacterial killing and suppress the emergence of resistance.

In particular, CTAP will use a dynamic in vitro hollow-fibre infection model (HFIM) to describe the effect of changing antibiotic concentrations on bacterial killing and the emergence of resistance.

The HFIM has emerged as a highly valuable pre-clinical drug development tool enabling simulation of human-like concentrations as well as high bacterial-loads – as seen in severe infections – which cannot be mimicked by the traditional animal models of infection.

Compared to other in vitro models, the HFIM is also superior allowing compartmentalisation of infection to enable more informative analysis.

The data generated from this model will describe the effect of standard and new dosing regimens on maximal bacterial killing and suppression of resistance.

Advanced mathematical modelling techniques will then be applied to combine the in vitro data describing exposure-response relationships with clinical data that define dose-exposure relationships, to propose new dosing regimens for clinical validation. 

In vitro hollow-fibre infection model that simulates PK in patients

In vitro hollow-fibre infection model that simulates PK in patients