Pharmacokinetic/pharmacodynamic modeling of anidulafungin time-kill curves against Candida considering antifungal resistance
Unai Caballero (1), Sandra Gil-Alonso (1), Elena Eraso (2), Guillermo Quindós (2), Elena Suarez (1), and Nerea Jauregizar(1)
(1) Department of Pharmacology, Faculty of Medicine, University of the Basque Country (UPV/EHU), Spain. UFI11/25 “Microbios y Salud. (2) Department of Immunology, Microbiology and Parasitology, Faculty of Medicine, University of the Basque Country (UPV/EHU), Spain. UFI11/25 “Microbios y Salud”
Objectives: Echinocandins are first-line agents to treat invasive candidiasis. However, resistance to these drugs is increasing. As pharmacokinetic/pharmacodynamic (PK/PD) modelling of in vitro data is an effective tool to describe the activity of antimicrobial drugs, the aim of this study was to develop a PK/PD model that described the activity of anidulafungin against Candida considering the emergence of resistant subpopulations.
Methods: In vitro static and dynamic time-kill (TK) experiments for anidulafungin against Candida were performed in triplicate. Concentrations assayed for the static experiments ranged from 0.0015 to 32 mg/L[1]; for the dynamic experiments, a single concentration of 5.47 mg/L was tested [2]. In both TK experiments, samples for viable counts were taken at 0, 2, 4, 6, 24 and 48 h. Several models explaining the reduced drug sensitivity were tested [3]. Data was modeled using NONMEM V7.3.0 with first order conditional estimation method Goodness of fit plots, change in OFV values and precision of parameter estimates were evaluated to assess model performance.
Results: Anidulafungin TK data were best described using a model that included a sensitive (S) subpopulation and a non-growing drug-resistant (R) fungal subpopulation, with a first- order transfer rate constant from S to R (KSR). A sigmoidal Emax model best described the drug effect, in which anidulafungin effect was included as an increase in the killing rate (Kd) of Candida in the S subpopulation. Both in static and dynamic models, the transfer rate from S to R was faster than the killing rate of anidulafungin (for C.albicans, KSR=0.17 h-1 static, Kd=0.0016 h-1 static, KSR=0.05 h-1 dynamic, Kd=0.0003 h-1 dynamic).
Conclusions: The developed model successfully described the activity of anidulafungin regarding less sensitive subpopulations of Candida. This kind of model development might be helpful in the design of dosing regimes that minimize antifungal resistance.
References:
[1] Gil-Alonso et al., IJAA 2016; 47:178-183
[2] Jauregizar N et al., Pharmacokinetic/Pharmacodynamic modeling of dynamic time-kill curves for anidulafungin against Candida. PAGE Poster presentation 2015. Crete, Greece.
[3] Nielsen EI, Friberg L. Pharmacol Rev 2013; 65:1053-90