Sven C van Dijkman1, Pieter A J G De Cock2,3, Koenraad Smets4, Wim Decaluwe5, Anne Smits6, Karel Allegaert7,8, Johan Vande Walle9, Peter De Paepe2, Oscar Della Pasqua10,11. 1. Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden, The Netherlands. 2. Heymans Institute of Pharmacology, Ghent University, Ghent, Belgium. 3. Department of Pharmacy, Ghent University Hospital, Ghent, Belgium. 4. Department of Neonatology, Ghent University Hospital, Ghent, Belgium. 5. Department of Neonatology, AZ Sint Jan Brugge-Oostende AV, Bruges, Belgium. 6. Neonatal Intensive Care Unit, University Hospital Leuven, Leuven, Belgium. 7. Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands. 8. Department of Development and Regeneration, KU Leuven, Leuven, Belgium. 9. Department of Paediatric Nephrology, Ghent University Hospital, Ghent, Belgium. 10. Clinical Pharmacology and Therapeutics, University College London, BMA House, Tavistock Square, London, WC1H 9JP, UK. o.dellapasqua@ucl.ac.uk. 11. Clinical Pharmacology Modelling & Simulation, GlaxoSmithKline, Uxbridge, UK. o.dellapasqua@ucl.ac.uk.
Abstract
PURPOSE: There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates. METHODS: A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study. RESULTS: Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA. CONCLUSIONS: The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population.
PURPOSE: There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates. METHODS: A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study. RESULTS: Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA. CONCLUSIONS: The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population.
Authors: Jolien J M Freriksen; Tjitske M van der Zanden; Inge G A Holsappel; Bouwe Molenbuur; Saskia N de Wildt Journal: Paediatr Drugs Date: 2022-03-28 Impact factor: 3.930
Authors: Camille E van Hoorn; Robert B Flint; Justin Skowno; Paul Davies; Thomas Engelhardt; Kirk Lalwani; Olutoyin Olutoye; Erwin Ista; Jurgen C de Graaff Journal: Eur J Clin Pharmacol Date: 2020-10-29 Impact factor: 2.953