Population Pharmacokinetic Modeling of Gentamicin in Pediatrics

The primary objective of this work was to characterize the pharmacokinetics (PK) of gentamicin across the whole pediatric age spectrum from premature neonates to young adults with a single model by identifying significant clinical predictors. A nonlinear mixed‐effect population PK model was develope...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of clinical pharmacology 2019-12, Vol.59 (12), p.1584-1596
Hauptverfasser: Wang, Hechuan, Sherwin, Catherine, Gobburu, Jogarao V.S., Ivaturi, Vijay
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The primary objective of this work was to characterize the pharmacokinetics (PK) of gentamicin across the whole pediatric age spectrum from premature neonates to young adults with a single model by identifying significant clinical predictors. A nonlinear mixed‐effect population PK model was developed with retrospective therapeutic drug‐monitoring data. A total of 6459 drug concentration measurements from 3370 hospitalized patients were collected for model building (n = 2357) and evaluation (n = 1013). In agreement with previously reported models, a 2‐compartment model with first‐order elimination best described the drug PK. Patient‐specific factors significantly impacting gentamicin clearance included fat‐free mass, postmenstrual age, and serum creatinine (SCr). Based on our model, the deviation of the individual SCr from the age‐dependent expected mean SCr value (SCrM) can result in a 40% lower clearance in a patient with renal impairment than that in a patient with normal kidney function, with SCrM:SCr ratios between 0.16 and 3.2 in this study. Consistent with the known age‐dependent changes of the proportion of extracellular water in body weight, the inclusion of the impact of extracellular water maturation on the central volume of distribution was found to improve the model fitting significantly. In comparison with other published models, model evaluation suggested the developed model was the least biased and physiologically most representative. These results will be used to inform individualized initial dosing strategies and serve as a prior PK model for Bayesian updating and forecasting as individual clinical observations become available.
ISSN:0091-2700
1552-4604
DOI:10.1002/jcph.1479