Mathematical pharmacodynamic modeling for antimicrobial assessment of ceftazidime/colistin versus gentamicin/meropenem combinations against carbapenem-resistant Pseudomonas aeruginosa biofilm

利用数学药效学模型评估头孢他啶/粘菌素联合用药与庆大霉素/美罗培南联合用药对抗耐碳青霉烯类铜绿假单胞菌生物膜的抗菌活性。

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Abstract

BACKGROUND: Carbapenem-resistant Pseudomonas aeruginosa (CRPA) represents an escalating healthcare hazard with high mortality worldwide, especially in presence of biofilm. The current study aimed to evaluate the anti-biofilm potentials of ceftazidime, colistin, gentamicin, and meropenem alone and in combinations against biofilm-forming CRPA. METHODS: Biofilm killing and checkerboard assay were performed to detect the effectiveness of combined antibiotics against biofilms and planktonic cells, respectively. The bacterial bioburden retrieved from the established biofilms following treatment with combined antibiotics was utilized to construct a three-dimensional response surface plot. A sigmoidal maximum effect model was applied to determine the pharmacodynamic parameters (maximal effect, median effective concentration, and Hill factor) of each antibiotic to create a mathematical three-dimensional response surface plot. RESULTS: Data revealed statistically significant (p < 0.05) superior anti-biofilm potential in the case of colistin followed by a lower effect in the case of gentamicin and meropenem, while ceftazidime exhibited the least anti-biofilm activity. The fractional inhibitory concentration index (FICI ≤ 0.5) indicated synergism following treatment with the combined antibiotics. An elevated anti-biofilm activity was recorded in the case of gentamicin/meropenem compared to ceftazidime/colistin. Synergistic anti-biofilm potentials were also detected via the simulated pharmacodynamic modeling, with higher anti-biofilm activity in the case of the in vitro observation compared to the simulated anti-biofilm profile. CONCLUSIONS: The present study highlighted the synergistic potentials of the tested antibiotic combinations against P. aeruginosa biofilms and the importance of the mathematical pharmacodynamic modeling in investigating the efficacy of antibiotics in combination as an effective strategy for successful antibiotic therapy to tackle the extensively growing resistance to the currently available antibiotics.

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