Adequate colistin exposure is important for microbiological clearance. This study was performed in critically ill patients >18 years old to develop a simplified nonparametric pharmacokinetic (PK) model of colistin for routine clinical use and to determine the role of dose optimization. The Non-Parametric Adaptive Grid algorithm within the Pmetrics software package for R was used to develop a PK model from 47 patients, and external validation of the final model was performed in 13 patients. A 1-compartment multiplicative gamma error model with 0-order input and first-order elimination of colistin was developed with creatinine clearance and serum albumin as covariates on elimination rate constant. An R2 for observed vs individual predicted colistin concentrations of 0.92 was obtained in the validation cohort. High interindividual variability in colistin steady-state area under the plasma concentration-time curve (AUC) from from 120 hours to 144 hours (coefficient of variation = 80.1%) and a high interoccasion variability (median coefficient of variation of AUC from time 0 to hours predicted every 8 hours for initial 96 hours after starting colistin = 23.8) was predicted in patients who received this antibiotic for a period of over 152 hours (n = 22). With the model-suggested dose regimen, only 20% of simulated profiles achieved AUC from time 0 to 24 hours in the range of 50 to 60 mg • h/L due to high variability in population PK. In this group of patients, steady-state colistin concentrations were predicted to be achieved >96 hours after initiation of colistimethate sodium. This study advocates the need for early and repeated therapeutic drug monitoring and dose optimization in critically ill patients to achieve adequate therapeutic concentration of colistin.
Keywords: Bayesian; albumin; colistin; pharmacokinetics; therapeutic drug monitoring.
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