A neonatal amikacin covariate model can be used to predict ontogeny of other drugs eliminated through glomerular filtration in neonates.
OBJECTIVE
Recently, a covariate model characterizing developmental changes in clearance of amikacin in neonates has been developed using birth bodyweight and postnatal age. The aim of this study was to evaluate whether this covariate model can be used to predict maturation in clearance of other renally excreted drugs.


METHODS
Five different neonatal datasets were available on netilmicin, vancomycin, tobramycin and gentamicin. The extensively validated covariate model for amikacin clearance was used to predict clearance of these drugs. In addition, independent reference models were developed based on a systematic covariate analysis.


RESULTS
The descriptive and predictive properties of the models developed using the amikacin covariate model were good, and fairly similar to the independent reference models (goodness-of-fit plots, NPDE). Moreover, similar clearance values were obtained for both approaches. Finally, the same covariates as in the covariate model of amikacin, i.e. birth bodyweight and postnatal age, were identified on clearance in the independent reference models.


CONCLUSIONS
This study shows that pediatric covariate models may contain physiological information since information derived from one drug can be used to describe other drugs. This semi-physiological approach may be used to optimize sparse data analysis and to derive individualized dosing algorithms for drugs in children.
Division of Pharmacology, LACDR, Leiden University, Leiden, The Netherlands.
Roosmarijn F W
RF
De Cock
Karel
K
Allegaert
Catherine M T
CM
Sherwin
Elisabet I
EI
Nielsen
Matthijs
M
de Hoog
Johannes N
JN
van den Anker
Meindert
M
Danhof
Catherijne A J
CA
Knibbe
D000583:Amikacin / Q000378:metabolism*; D000900:Anti-Bacterial Agents / Q000378:metabolism*; D005919:Glomerular Filtration Rate; D006801:Humans; D007231:Infant, Newborn; D007668:Kidney / Q000502:physiology*; D008657:Metabolic Clearance Rate; D008954:Models, Biological
D000900:Anti-Bacterial Agents; D000583:Amikacin