PKPD models for colistin and meropenem on a wild-type and a resistant strain of Pseudomonas aeruginosa

Abstract: Resistant bacteria are becoming more and more of a problem but treatment with antibiotics in combination may overcome and prevent resistance development. The combination of meropenem and colistin against Pseudomonas aeruginosa has been proposed as a promising treatment to increase the bactericidal effect and a synergistic effect has been proposed. A Pharmacokinetic-Parmacodynamic (PKPD) model that describes the dynamics of bacteria kill could be used to evaluate if the effects are additive or not. The model could later also be used to find optimal dosing for both of the antibiotics used alone or in combination with each other. The aim of the present study was to develop a PKPD model that describes the bactericidal activity of the two antibiotics, both in mono-therapy and in combination. The data were from in vitro static time kill-curve experiments that had been conducted on two strains of Pseudomonas aeruginosa; the wild-type (ATCC 27853) and the resistant-type (PL0603761). Resistance was observed in the experimental data and thus it had to be taken into account in the modelling. PKPD models were fitted to the bacterial counts in NONMEM with pharmacodynamic compartments for susceptible and resting bacteria. In the resting compartment the bacteria could not be killed. The bacteria moved into the resting compartment from the susceptible compartment when a certain concentration of bacteria was obtained. A pharmacokinetic compartment characterized changes in drug concentrations and the drug degradation during the experimental time was considered. Two different drug effects were tried on the susceptible bacteria, linear effect and Emax models.. The resistance development occurring during the experiments was described by two compartments where the parameter kon determined the rate of onset of resistance development. In the final model, kon was found to either be concentration-independent or dependent, depending on antibiotics and bacteria. The degree of resistance development produced an overall inhibitory effect on the drug effect. The growth rate was estimated to be lower and the EC50 to be higher for the resistant compared to the wild-type bacteria. The model was used to predict the expected time-kill curve if the effect of the two drugs are additive when combining the two drugs. The observed  bacteria kill was lower than the model predicted for the wild-type bacteria. For the resistant bacteria the assumption of additive bacteria kill for the two drugs-seemed adequate.