2016-07-27 23:00:00
Funding for: UK Students, EU Students.
Funding amount: Not specified.
Antimicrobial resistance is a global concern that interests human and animal health. Identification of the optimal dose for antimicrobial drugs (AMD) against pathogens is a current priority. Therapeutic success is likely if susceptible bacteria are exposed to doses of AMD that translate in vivo into sufficiently high plasma concentrations that are sustained for a sufficient time.
For dose optimisation, three key components are required: (1) the pharmacokinetics in the target host, (2) the range of susceptibility of bacteria encountered in the field (Minimal Inhibitory Concentration MIC), (3) the relationship between AMD concentrations, the MIC value and the antimicrobial effect (PK/PD index).
While points (1) and (2) are well known, the optimal PK/PD indices in veterinary species are mainly unknown. Until now, the PK/PD indices were either extrapolated from other species (mouse infection models) or from in vitro bacterial-kill assays that only expose a known bacterial inoculum to fixed concentrations of AMD. The latter have been superseded by Hollow Fibre Infection Models (HFIM) that have recently received regulatory approval to support AMD innovations in people. This in vitro system mimics real-time changes in concentration without loss of bacteria from the culture and allows mathematical modelling of pharmacodynamics with changing concentrations.
The aim of this project is to validate the HFIM for dynamic evaluation of antimicrobial efficacy against veterinary pathogens, taking the example of tetracyclines. Tetracyclines represent the highest tonnage of veterinary AMR sold in the UK but the mechanisms of their antimicrobial activity are not completely understood.
We have 4 objectives:
The outcome of this study is to demonstrate that the HFIM can address crucial questions in the field of veterinary therapeutics, while reducing animal use. The student will be supported
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