ABSTRACT
Objective: For meropenem 40%T > MIC is associated with optimal killing of P. aeruginosa and E. coli. However, it is unknown how the distribution of %T > MIC through a treatment day impacts the antimicrobial effect in vitro. Therefore, we investigated the in vitro antibiotic activity of meropenem, precisely if 40%T > MIC is achieved in one single long period (single dose), 2 × 20% periods (dosing-bid), or 3 × 13.3% (dosing t.i.d.) thereby keeping the overall period of T > MIC constant. Material/Methods: Time kill curves (TKC) with P. aeruginosa-ATCC-27853 and E. coli-ATCC-25922 and five clinical isolates each were implemented over 24 h in CAMHB with concentrations from 0.25×MIC-32×MIC. Periods over and under MIC were simulated by centrifugation steps (discarding supernatant and refilling with fresh CAMHB). Double and triple dosing involved further addition and removal of antibiotic. Complementary growth controls (GC) with and without centrifugation steps were done and the emergence of phenotypical resistance was evaluated (repeated MIC-testing after antibiotic administration). Results: No impact of centrifugation on bacterial growth was seen. TKC with P. aeruginosa showed the best killing in the triple dosage, followed by the double and single dose. In multiple regimens at least a concentration of 4×MIC was needed to achieve a recommended 2-3 log10 killing. Likewise, a reduction of E. coli was best within the three short periods. Contrary to the TKCs with P. aeruginosa we could observe that after the inoculum reached a certain CFU/mL (≥10^8), no further addition of antibiotic could achieve bacterial killing (identified as the inoculum effect). For P. aeruginosa isolates resistance appeared within all regimens, the most pronounced was found in the 40%T > MIC experiments indicating that a single long period might accelerate the emergence of resistance. Contrary, for E. coli no emergence of resistance was found. Conclusion/Outlook: We could show that not solely the %T > MIC is decisive for an efficient bacterial eradication in vitro, but also the distribution of the selected %T > MIC. Thus, dividing the 40%T > MIC in three short periods requested lowers antibiotic concentrations to achieve efficient bacterial killing and reduces the emergence of resistance in P. aeruginosa isolates. The distribution of the %T > MIC did impact the bacterial eradication of susceptible pathogens in vitro and might play an even bigger role in infections with intermediate or resistant pathogens.
ABSTRACT
OBJECTIVES: Pharmacokinetic-pharmacodynamic (PK-PD) considerations are at the heart of defining susceptibility breakpoints for antibiotic therapy. However, current approaches follow a fragmented workflow. The aim of this study was to develop an integrative pharmacometric approach to define MIC-based breakpoints for killing and suppression of resistance development for plasma and tissue sites, integrating clinical microdialysis data as well as in vitro time-kill curves and heteroresistance information, exemplified by moxifloxacin against Staphylococcus aureus and Escherichia coli. METHODS: Plasma and target site samples were collected from ten patients receiving 400 mg moxifloxacin/day. In vitro time-kill studies with three S. aureus and two E. coli strains were performed and resistant subpopulations were quantified. Using these data, a hybrid physiologically based (PB) PK model and a PK-PD model were developed, and utilized to predict site-specific breakpoints. RESULTS: For both bacterial species, the predicted MIC breakpoint for stasis at 400 mg/day was 0.25 mg/L. Less reliable killing was predicted for E. coli in subcutaneous tissues where the breakpoint was 0.125 mg/L. The breakpoint for resistance suppression was 0.06 mg/L. Notably, amplification of resistant subpopulations was highest at the clinical breakpoint of 0.25 mg/L. High-dose moxifloxacin (800 mg/day) increased all breakpoints by one MIC tier. CONCLUSIONS: An efficient pharmacometric approach to define susceptibility breakpoints was developed; this has the potential to streamline the process of breakpoint determination. Thereby, the approach provided additional insight into target site PK-PD and resistance development for moxifloxacin. Application of the approach to further drugs is warranted.