Optimization of Synergistic Combination Regimens against Carbapenem- and Aminoglycoside-Resistant Clinical Pseudomonas aeruginosa Isolates via Mechanism-Based Pharmacokinetic/Pharmacodynamic Modeling.
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, 107.5CFU/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 MICtobramycinof 32 mg/liter, i.e., both 98th percentiles according to the EUCAST database). Against this isolate, imipenem (1.5× MIC) combined with 1 to 2 mg/liter tobramycin (MIC, 32 mg/liter) or amikacin (MIC, 4 mg/liter) yielded ≥2-log10more killing than the most active monotherapy at 48 h and prevented resistance. For all three strains, synergistic killing without resistance was achieved by ≥0.88× MICimipenemin combination with a median of 0.75× MICtobramycin(range, 0.032× to 2.0× MICtobramycin) or 0.50× MICamikacin(range, 0.25× to 0.50× 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-log10killing and prevent regrowth at 48 h in 90.3% of patients (median bacterial killing, >4.0 log10CFU/ml) against double-resistant isolate FADDI-PA088 and therefore was highly promising.
Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.
Rajbharan
R
Yadav
Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA jbulitta@cop.ufl.edu Cornelia.Landersdorfer@monash.edu.
Jürgen B
JB
Bulitta
Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.
Roger L
RL
Nation
Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia jbulitta@cop.ufl.edu Cornelia.Landersdorfer@monash.edu.|Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.|School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Cornelia B
CB
Landersdorfer
D000583:Amikacin / Q000494:pharmacology; D000617:Aminoglycosides / Q000494:pharmacology*; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D015780:Carbapenems / Q000494:pharmacology*; D004357:Drug Synergism; D015378:Imipenem / Q000494:pharmacology; D008826:Microbial Sensitivity Tests; D008962:Models, Theoretical; D009010:Monte Carlo Method; D011550:Pseudomonas aeruginosa / Q000187:drug effects*; D014031:Tobramycin / Q000494:pharmacology
D000617:Aminoglycosides; D000900:Anti-Bacterial Agents; D015780:Carbapenems; D015378:Imipenem; D000583:Amikacin; D014031:Tobramycin
Monte Carlo simulations; amikacin; imipenem; mathematical modeling; population pharmacokinetics and pharmacodynamics; synergy; tobramycin