O26 Population pharmacokinetic meta-analysis of individual data to design the first randomized efficacy trial of vancomycin in neonates and young Infants

BackgroundIn the absence of consensus, the present meta-analysis was performed to determine an optimal dosing regimen of vancomycin for neonates.MethodsA ‘meta-model’ using NONMEM with 4894 concentrations from 1631 neonates was built and Monte Carlo simulations were performed to design an optimal in...

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Published inArchives of disease in childhood Vol. 104; no. 6; pp. e11 - e12
Main Authors Jacqz-Aigrain, E, Leroux, S, Thomson, AH, Allegaert, K, Capparelli, EV, Biran, V, Simon, N, Meibohm, B, Y-L, Lo, Marqués, R, Peris, J-E, Lutsar, I, Saito, J, Nayamura, H, van den Anker, JN, Sharland, M, Zhao, W
Format Journal Article
LanguageEnglish
Published London BMJ Publishing Group LTD 01.06.2019
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Summary:BackgroundIn the absence of consensus, the present meta-analysis was performed to determine an optimal dosing regimen of vancomycin for neonates.MethodsA ‘meta-model’ using NONMEM with 4894 concentrations from 1631 neonates was built and Monte Carlo simulations were performed to design an optimal intermittent infusion, aiming at reaching a target AUC0-24 of 400 mg*h/L at steady state in at least 80% of neonates.ResultsA two-compartment model best fitted the data. Current weight, post-menstrual age (PMA) and serum creatinine were the significant covariates for clearance (CL). After model validation, simulations showed that a loading dose (25 mg/kg) and a maintenance dose (15 mg/kg twice daily if < 35 weeks PMA and 15 mg/kg three times daily if ≥ 35 weeks PMA) achieved the AUC0-24 target earlier than a standard ‘Blue Book’ dosage regimen in more than 89% of the treated patients.ConclusionsThe results of a population meta-analysis of vancomycin data have been used to develop a new dosing regimen for neonatal use and assist in the design of the model-based, multinational European trial, NeoVanc.Disclosure(s)Nothing to disclose
ISSN:0003-9888
1468-2044
DOI:10.1136/archdischild-2019-esdppp.26