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Model-based clinical dose optimization for phenobarbital in neonates: An illustration of the importance of data sharing and external validation
S. Völler, RB. Flint, LM. Stolk, PLJ. Degraeuwe, SHP. Simons, P. Pokorna, DM. Burger, R. de Groot, D. Tibboel, CAJ. Knibbe, . ,
Language English Country Netherlands
Document type Journal Article
- MeSH
- Phenobarbital administration & dosage MeSH
- Infant MeSH
- Humans MeSH
- Drug Monitoring methods MeSH
- Infant, Premature MeSH
- Infant, Newborn MeSH
- Prospective Studies MeSH
- Information Dissemination methods MeSH
- Dose-Response Relationship, Drug MeSH
- Check Tag
- Infant MeSH
- Humans MeSH
- Male MeSH
- Infant, Newborn MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: Particularly in the pediatric clinical pharmacology field, data-sharing offers the possibility of making the most of all available data. In this study, we utilize previously collected therapeutic drug monitoring (TDM) data of term and preterm newborns to develop a population pharmacokinetic model for phenobarbital. We externally validate the model using prospective phenobarbital data from an ongoing pharmacokinetic study in preterm neonates. METHODS: TDM data from 53 neonates (gestational age (GA): 37 (24-42) weeks, bodyweight: 2.7 (0.45-4.5) kg; postnatal age (PNA): 4.5 (0-22) days) contained information on dosage histories, concentration and covariate data (including birth weight, actual weight, post-natal age (PNA), postmenstrual age, GA, sex, liver and kidney function, APGAR-score). Model development was carried out using NONMEM® 7.3. After assessment of model fit, the model was validated using data of 17 neonates included in the DINO (Drug dosage Improvement in NeOnates)-study. RESULTS: Modelling of 229 plasma concentrations, ranging from 3.2 to 75.2mg/L, resulted in a one compartment model for phenobarbital. Clearance (CL) and volume (Vd) for a child with a birthweight of 2.6kg at PNA day 4.5 was 0.0091L/h (9%) and 2.38L (5%), respectively. Birthweight and PNA were the best predictors for CL maturation, increasing CL by 36.7% per kg birthweight and 5.3% per postnatal day of living, respectively. The best predictor for the increase in Vd was actual bodyweight (0.31L/kg). External validation showed that the model can adequately predict the pharmacokinetics in a prospective study. CONCLUSION: Data-sharing can help to successfully develop and validate population pharmacokinetic models in neonates. From the results it seems that both PNA and bodyweight are required to guide dosing of phenobarbital in term and preterm neonates.
Department of Clinical Pharmacy Maastricht UMC The Netherlands
Department of Clinical Pharmacy St Antonius Hospital Nieuwegein The Netherlands
Department of Pediatrics Division of Neonatology Maastricht UMC Maastricht The Netherlands
Department of Pharmacy Erasmus Medical Center Rotterdam The Netherlands
References provided by Crossref.org
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- $a Völler, Swantje $u Division of Pharmacology, Leiden Academic Center for Drug Research, Gorlaeus Laboratories, Einsteinweg 55, 2333 CC Leiden, The Netherlands. Electronic address: s.voller@lacdr.leidenuniv.nl.
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- $a BACKGROUND: Particularly in the pediatric clinical pharmacology field, data-sharing offers the possibility of making the most of all available data. In this study, we utilize previously collected therapeutic drug monitoring (TDM) data of term and preterm newborns to develop a population pharmacokinetic model for phenobarbital. We externally validate the model using prospective phenobarbital data from an ongoing pharmacokinetic study in preterm neonates. METHODS: TDM data from 53 neonates (gestational age (GA): 37 (24-42) weeks, bodyweight: 2.7 (0.45-4.5) kg; postnatal age (PNA): 4.5 (0-22) days) contained information on dosage histories, concentration and covariate data (including birth weight, actual weight, post-natal age (PNA), postmenstrual age, GA, sex, liver and kidney function, APGAR-score). Model development was carried out using NONMEM® 7.3. After assessment of model fit, the model was validated using data of 17 neonates included in the DINO (Drug dosage Improvement in NeOnates)-study. RESULTS: Modelling of 229 plasma concentrations, ranging from 3.2 to 75.2mg/L, resulted in a one compartment model for phenobarbital. Clearance (CL) and volume (Vd) for a child with a birthweight of 2.6kg at PNA day 4.5 was 0.0091L/h (9%) and 2.38L (5%), respectively. Birthweight and PNA were the best predictors for CL maturation, increasing CL by 36.7% per kg birthweight and 5.3% per postnatal day of living, respectively. The best predictor for the increase in Vd was actual bodyweight (0.31L/kg). External validation showed that the model can adequately predict the pharmacokinetics in a prospective study. CONCLUSION: Data-sharing can help to successfully develop and validate population pharmacokinetic models in neonates. From the results it seems that both PNA and bodyweight are required to guide dosing of phenobarbital in term and preterm neonates.
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- $a Flint, Robert B $u Department of Pediatrics, Division of Neonatology, Erasmus MC - Sophia Children's Hospital, Rotterdam, The Netherlands; Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands; Department of Pharmacy, Erasmus Medical Center, Rotterdam, The Netherlands.
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