2015 - Hersonissos, Crete - Greece

PAGE 2015: Drug Resistance in Infection Modelling
Joe Standing

Treating Resistant Gram-Negatives: Bedside to Bench and Back

Lynette Phee (1,2), Yucheng Sheng (3), David Wareham (1,2), Joseph F Standing (4,5)

(1) Antimicrobial Research Group, Blizard Institute, Barts and The London School of Medicine and Dentistry, UK (2) Division of Infection, Barts Health NHS Trust, UK (3) School of Pharmacy, University College London, UK (4) Institute of Child Health, University College London, UK (5) Great Ormond Street Hospital, London, UK

Objective: London is a culturally diverse city, and this extends to diversity in bacterial pathogens. Multi-drug resistant (MDR) Gram-negatives are an increasing problem. We started at the bedside identifying a number of MDR A. baumannii clinical isolates. Moving to the bench, potentially synergistic combinations were identified with in vitro models and then tested in an invertebrate model of infection (G. mellonella). Returning to the bedside, we have used the identified combination to treat patients infected with extensively resistant strains of A. baumannii. Here we focus on the development of simple, identifiable mechanistic models which allowed for quantifying antimicrobial synergy and dose optimisation.

Methods: Colistin disrupts the outer membrane of Gram-negatives; it was therefore screened in combination with a range (10 agents) of Gram-positive agents using disk diffusion screening assay. Potential synergy was confirmed with checkerboard assays (1) and modelled with a response surface approach. Then ascending concentration 24 hour time-kill experiments with each drug alone and a range of combination concentrations was performed. Differential equation models (2) of colony-forming unit (CFU) concentration with time were extended to two drugs and simultaneous analysis of six strains (population approach) using NONMEM 7.3 (FOCE). A colistin concentration-dependent mechanistic synergy function was tested. Confirmation of combination efficacy was sought from G. mellonella infected with A. baumannii with survival modelled by time-to-event. Published PK models were used to optimise dose defined with a model-based utility function. Clinical outcome can be reported for two patients so far.

Results: Colistin-fusidic acid was identified as the optimal combination in initial screening. A simple model with time-varying effect adequately described time and concentration dependant resistance development. Adding a synergy term on resistance development rate significantly improved model fit (delta OFV 118).  Preliminary exploration of methods for dose optimisation by utility function have been explored.

Conclusions: We have shown both in vitro and in vivo that fusidic acid can be combined with colistin to treat MDR A. baumannii. Fusidic acid is potentially colistin-sparing and future work will investigate the combination activity versus other organisms.

[1] Moody J. Synergism testing: Broth microdilution checkerboard and broth macrodilution methods. Clinical Microbiology Procedures Handbook Vol. 2: American Society of Microbiology Press, Washington, D.C., 2004:
[2] Nielsen EI, Friberg LE. Pharmacokinetic-pharmacodynamic modeling of antibacterial drugs. Pharmacol Rev. 2013 Jun 26;65(3):1053-90.

Reference: PAGE 24 (2015) Abstr 3582 [www.page-meeting.org/?abstract=3582]
Oral: Drug Resistance in Infection Modelling
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