Optimizing antibiotic combinations is promising to combat multidrug-resistant Pseudomonas aeruginosa. This study aimed to systematically evaluate synergistic bacterial killing and prevention of resistance by carbapenem and aminoglycoside combinations and to rationally optimize combination dosage regimens via a mechanism-based mathematical model (MBM). We studied monotherapies and combinations of imipenem with tobramycin or amikacin against three difficult-to-treat double-resistant clinical P. aeruginosa isolates. Viable-count profiles of total and resistant populations were quantified in 48-h static-concentration time-kill studies (inoculum, 107.5 CFU/ml). We rationally optimized combination dosage regimens via MBM and Monte Carlo simulations against isolate FADDI-PA088 (MIC of imipenem [MICimipenem] of 16 mg/liter and MICtobramycin of 32 mg/liter, i.e., both 98th percentiles according to the EUCAST database). Against this isolate, imipenem (1.5x MIC) combined with 1 to 2 mg/liter tobramycin (MIC, 32 mg/liter) or amikacin (MIC, 4 mg/liter) yielded ≥2-log10 more killing than the most active monotherapy at 48 h and prevented resistance. For all three strains, synergistic killing without resistance was achieved by ≥0.88x MICimipenem in combination with a median of 0.75x MICtobramycin (range, 0.032x to 2.0x MICtobramycin) or 0.50x MICamikacin (range, 0.25x to 0.50x MICamikacin). The MBM indicated that aminoglycosides significantly enhanced the imipenem target site concentration up to 3-fold; achieving 50% of this synergistic effect required aminoglycoside concentrations of 1.34 mg/liter (if the aminoglycoside MIC was 4 mg/liter) and 4.88 mg/liter (for MICs of 8 to 32 mg/liter). An optimized combination regimen (continuous infusion of imipenem at 5 g/day plus a 0.5-h infusion with 7 mg/kg of body weight tobramycin) was predicted to achieve >2.0-log10 killing and prevent regrowth at 48 h in 90.3% of patients (median bacterial killing, >4.0 log10 CFU/ml) against double-resistant isolate FADDI-PA088 and therefore was highly promising.
- Mathematical modeling
- Monte Carlo simulations
- Population pharmacokinetics and pharmacodynamics