Model-Informed Translation of In Vitro Effects of Short-, Prolonged- and Continuous-Infusion Meropenem against Pseudomonas aeruginosa to Clinical Settings

Abstract

Pharmacokinetic-pharmacodynamic (PKPD) models have met increasing interest as tools to identify potential efficacious antibiotic dosing regimens in vitro and in vivo. We sought to investigate the impact of diversely shaped clinical pharmacokinetic profiles of meropenem on the growth/killing patterns of Pseudomonas aeruginosa (ARU552, MIC = 16 mg/L) over time using a semi-mechanistic PKPD model and a PK/PD index-based approach. Bacterial growth/killing were driven by the PK profiles of six patient populations (infected adults, burns, critically ill, neurosurgery, obese patients) given varied pathogen features (e.g., EC50, growth rate, inoculum), patient characteristics (e.g., creatinine clearance), and ten dosing regimens (including two dose levels and 0.5-h, 3-h and continuous-infusion regimens). Conclusions regarding the most favourable dosing regimen depended on the assessment of (i) the total bacterial load or fT>MIC (time that unbound concentrations exceed the minimum inhibitory concentration); (ii) the median or P0.95 profile of the population; and (iii) 8 h or 24 h time points. Continuous infusion plus loading dose as well as 3-h infusions (3-h infusions: e.g., for scenarios associated with low meropenem concentrations, P0.95 profiles, and MIC ≥ 16 mg/L) appeared superior to standard 0.5-h infusions at 24 h. The developed platform can serve to identify promising strategies of efficacious dosing for clinical trials.

Keywords: PK/PD index; PKPD model; Pseudomonas aeruginosa; beta-lactam; continuous infusion; meropenem; pharmacometrics; prolonged infusion; time-kill curve.

Figure 1

Total bacterial load (B_tot, a,b) and fT_>MIC (time that meropenem concentrations exceed the minimum inhibitory concentration, Figures (c,d)) reached by 95% (a,c) or 50% (b,d) of the patient (pat.) population at 24 h after start of therapy given different scenarios. Sepsis I: Delattre et al. [23]; Sepsis II: Roberts et al. [22] (no renal dysfunction); EC₅₀: drug concentration that produces 50% of E_max (maximum achievable kill rate constant); CLCR: creatinine clearance; kgrowth: rate constant of bacterial growth; kdeath: rate constant of natural bacterial death; higher inoculum: initial bacterial load of 8 log10 CFU/mL, either assumed to be susceptible or with an initial fraction in the resting state; scenarios marked with an asterisk * refer to a mixed adult population (default scenario; Li et al. [21]); CI: continuous infusion; LD: loading dose; q8h: every 8 h.

Figure 2

Total bacterial load versus fT_>MIC (time that meropenem concentrations exceed the minimum inhibitory concentration) reached by 95% (P_0.95, panel a) or 50% (median, panel b) of the patient population at 24 h after start of therapy given different scenarios. Sepsis I: Delattre et al. [23]; Sepsis II: Roberts et al. [22] (no renal dysfunction); EC₅₀: drug concentration that produces 50% of E_max (maximum achievable kill rate constant); CLCR: creatinine clearance; k_growth: rate constant of bacterial growth; k_death: rate constant of natural bacterial death; higher inoculum: initial bacterial load of 8 log10 CFU/mL, either assumed to be susceptible or with an initial fraction in the resting state; scenarios marked with an asterisk * refer to a mixed adult population (default scenario; Li et al. [21]); CI: continuous infusion; LD: loading dose; q8h: every eight hours.

Figure 3

PKPD model-based output assessed for each scenario, exemplified by the default adult infected population (Li et al. [21]) and a 0.5h_TDD6000mg (2000 mg every 8 h) dosing regimen. Total bacterial load (B_tot) and fT_>MIC (time that unbound meropenem concentrations exceed the minimum inhibitory concentration; here: MIC = 16 mg/L) were assessed at 8 h and at 24 h after start of antibiotic treatment. P_0.95: profile representing the 95th percentile in the population at a given time point; dashed lines mark the minimum inhibitory concentration of the ARU552 strain (upper panel) and the initial bacterial load/bacteriostasis (lower panel).