Predictive Performance of a Vancomycin Population Pharmacokinetic Model in Neonates

INTRODUCTION The pharmacokinetics of vancomycin are highly variable among neonates, which makes dosing challenging in this population. However, adequate drug exposure is critical, especially when treating methicillin-resistant Staphylococcus aureus (MRSA) infections. Utilization of population pharmacokinetic models and Bayesian methods offers the potential for developing individualized therapeutic approaches. To meet this need, a neonatal vancomycin population pharmacokinetic model was recently published. The current study sought to externally evaluate the predictive performance and generalizability of this model. METHODS A retrospective chart review of neonates who received vancomycin and had ≥1 peak and ≥1 trough concentrations at five Intermountain Healthcare neonatal intensive care units from 2006 to 2013 was performed and served as the external validation cohort. The published population pharmacokinetic model was implemented in NONMEM 7.2 with the structural and variance parameter values set equal to the estimates reported previously. The model was then used to predict the first peak and trough concentration for each neonate in the validation cohort and the model prediction error and absolute prediction error were calculated. Normalized prediction distribution errors (NPDE) were also evaluated. RESULTS A total of 243 neonates were studied with a median postmenstrual age of 33 (range: 23-54) weeks and a median weight of 1.6 (range: 0.4-6.8) kg. The model predicted the observed vancomycin concentrations with reasonable precision. For all vancomycin concentrations, the median prediction error was -0.8 (95% CI: -1.4 to -0.4) mg/L and the median absolute prediction error was 3.0 (95% CI: 2.7-3.5) mg/L. No trends in NPDE across weight, postmenstrual age, serum creatinine, or time after dose were observed. CONCLUSION An evaluation of a recently published neonatal vancomycin population pharmacokinetic model in a large external dataset supported the predictive performance and generalizability of the model. This model may be useful in evaluating neonatal vancomycin dosing regimens and estimating the extent of drug exposure.