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Comparative pharmacodynamics and dose optimization of liposomal amphotericin B against Candida species in an in vitro pharmacokinetic/pharmacodynamic model.

Maria-Ioanna BeredakiMaiken Cavling ArendrupSpyros PournarasJoseph Meletiadis
Published in: Antimicrobial agents and chemotherapy (2024)
As comparative pharmacokinetic/pharmacodynamic (PK/PD) studies of liposomal amphotericin B (L-AMB) against Candida spp. are lacking, we explored L-AMB pharmacodynamics against different Candida species in an in vitro PK/PD dilution model. Eight Candida glabrata , Candida parapsilosis , and Candida krusei isolates (EUCAST/CLSI AMB MIC 0.125-1 mg/L) were studied in the in vitro PK/PD model simulating L-AMB C max = 0.25-64 mg/L and t 1/2 = 9 h. The model was validated with one susceptible and one resistant Candida albicans isolate. The C max /MIC-log 10 CFU/mL reduction from the initial inoculum was analyzed with the E max model, and Monte Carlo analysis was performed for the standard (3 mg/kg with C max = 21.87 ± 12.47 mg/L) and higher (5 mg/kg with C max = 83 ± 35.2 mg/L) L-AMB dose. A ≥1.5 log 10 CFU/mL reduction was found at L-AMB C max = 8 mg/L against C. albicans , C. parapsilosis , and C. krusei isolates (MIC 0.25-0.5 mg/L) whereas L-AMB C max ≥ 32 mg/L was required for C. glabrata isolates. The in vitro PK/PD relationship followed a sigmoidal pattern ( R 2 ≥ 0.85) with a mean C max /MIC required for stasis of 2.1 for C. albicans (close to the in vivo stasis), 24/17 (EUCAST/CLSI) for C. glabrata , 8 for C. parapsilosis , and 10 for C. krusei . The probability of target attainment was ≥99% for C. albicans wild-type (WT) isolates with 3 mg/kg and for wild-type isolates of the other species with 5 mg/kg. L-AMB was four- to eightfold less active against the included non- C . albicans species than C. albicans . A standard 3-mg/kg dose is pharmacodynamically sufficient for C. albicans whereas our data suggest that 5 mg/kg may be recommendable for the included non- C . albicans species.
Keyphrases
  • candida albicans
  • biofilm formation
  • genetic diversity
  • wild type
  • escherichia coli
  • machine learning
  • pseudomonas aeruginosa
  • cystic fibrosis
  • electronic health record
  • big data