PHARMACOKINETIC STUDIES IN NEONATES: IS AN OPPORTUNISTIC SAMPLING STRATEGY SUFFICIENT FOR POPULATION PHARMACOKINETIC MODELLING AND DOSE PREDICTION?. Issue 1 (14th December 2015)

• Record Type: Journal Article
• Authors: Leroux, Stéphanie; Turner, Mark A.; Guellec, Chantal Barin-Le; Hill, Helen; Anker, Johannes N. van den; Kearns, Gregory L.; Jacqz-Aigrain, Evelyne; Zhao, Wei
• Is Part Of: Archives of disease in childhood. Volume 101:Issue 1(2016)
• Page Start: e1
• Page End: e1
• Publication Date: 2015-12-14
• Subjects: ESDP; Children -- Diseases -- Periodicals; Infants -- Diseases -- Periodicals; 618.920005
• DOI: 10.1136/archdischild-2015-310148.19
• Languages: English
• ISSNs: 0003-9888

Abstract

Abstract : Background and objective: The use of an opportunistic (also called scavenged) sampling strategy in a prospective pharmacokinetic study combined with population pharmacokinetic modelling has been proposed as an alternative strategy to conventional methods for accomplishing pharmacokinetic studies in neonates. However, the reliability of this approach in this particular paediatric population has not been evaluated. The objective of the present study was to evaluate the performance of an opportunistic sampling strategy for a population pharmacokinetic estimation as well as dose prediction, and compare this strategy to a pre-determined pharmacokinetic sampling approach. Methods: Three population pharmacokinetic models were derived for ciprofloxacin from opportunistic blood samples (SC model), pre-determined (i.e., scheduled) samples (TR model) and all samples (full model used to previously characterize ciprofloxacin pharmacokinetics), respectively, using NONMEM software. The predictive performance of developed models was evaluated in an independent group of patients. Results: Pharmacokinetic data from 60 newborns were obtained with a total of 430 samples available for analysis; 265 collected at pre-determined times and 165 that were scavenged from those obtained as part of clinical care. All data sets were fit using a two-compartment model with first order elimination. The SC model could identify the most significant covariates and provided reasonable estimates of population pharmacokinetic parameters (clearance and steady state volume of distribution) as compared to the TR and full models. Their predictive performances were further confirmed in an external validation by Bayesian estimation and showed similar results. Monte Carlo simulation based on AUC0–24 /MIC using either the SC or the TR model gave similar dose prediction for ciprofloxacin. Conclusion: Blood samples scavenged in the course of caring for neonates can be used to estimate ciprofloxacin pharmacokinetic parameters and therapeutic dose requirements.