Maddlie Bardol (1), Antje Neubert (2), Yucheng Sheng (1), Brian Anderson (3), Peter Larsson (4), Irmgard Toni (2), Dick Tibboel (5), Tuuli Metsvaht (6), Joe Standing (1) on behalf of the CloSed consortium
(1) Infection, Inflammation and Rheumatology Section, UCL Great Ormond Street Institute of Child Heath, University College London, London, UK (2) Department of Paediatrics and Adolescent Medicine, Universitätsklinikum Erlangen, Erlangen, Germany (3) Department of Anaesthesia, University of Auckland, New Zealand (4) Paediatric Intensive Care Unit, Karolinska University Hospital, Stockholm, Sweden (5) Paediatric Intensive Care, Erasmus University Rotterdam, Netherlands (6) Neonatal Intensive Care, University of Tartu, Estonia
Objectives: These PK results are part of a PK/PD/PG analysis for the CloSed trial: a double blind, randomised, active-controlled phase III trial with parallel groups which aimed to assess the non inferiority of clonidine compared to midazolam in mechanically ventilated children in PICU [1]. The objectives of this PK study were to develop population PK models for clonidine, midazolam and morphine and test the influence of covariates (weight, age, liver function, creatinine) and genetic variants on the PK.
Methods: Twenty-eight children who received the investigational medicinal products (IMP) were included in the PK analysis: 13 receiving midazolam and 15 receiving clonidine. The median postmentrual age (PMA) and weight (BW) of the population were 44 weeks and 4 kg, respectively. The IMP were administered as continuous infusion with 15 minutes loading dose followed by maintenance infusion (7 days maximum). Doses were adjusted following an algorithm based on sedation scores. In addition to IMP, all patients received morphine as background for pain and the the dose was adjusted using pain scores. Population pharmacokinetic modelling was undertaken with NONMEM 7.4. BW and PMA were included a priori in the models using an allometric weight scaling (exponent fixed to 0.75 for clearances and 1 for volumes of distribution) and a maturation function, respectively [2]. In addition, the influence of covariates evaluating the liver function and creatinine were tested on the clearances. The effect of genetic variants was also tested on the individual clearances using linear regression with PLINK 1.9. Twenty genetic variants from genes coding for metabolism enzymes or receptors were explored. The final models were evaluated using visual predictive check (VPC).
Results: For clonidine and midazolam, the clearances were best scaled with allometry and by fixing the parameters of the sigmoidal maturation functions using previous studies [2,3]. The concentration of clonidine was best described by a one-compartment model. The estimates of the PK parameters standardized to 70 kg (with RSE) were: Clearance (CL) = 28 L/h (20%) and central volume of distribution (V1)= 202 L (24%). Interindividual variability (IIV) was included on the CL (49%) and V1 (87%). A one-compartment model for the parent and the metabolite 1-hydroxymidazolam (1-OH-M) provided best fit for midazolam. The estimates (standardized to 70 kg) were: parent central volume of distribution (V1)= 89 L (30%), formation clearance to 1-OH-M (CLm) = 33.4 L/h (32%), volume of distribution for 1-OH-M (Vm)= 90.8 L (68%), elimination clearance of 1-OH-M (CLom)= 212 L/h (12%). IIV was included on Clm (91%) and V1 (133%). No significant influence of other covariates was found for either clonidine or midazolam. Two different maturation functions were used to describe the metabolite formation clearances and their elimination clearances for morphine [4]. A maturation function was also included on the central volume of distribution [5]. Maturation functions were fixed to reported estimates [4,5]. The model that best described the data was a one-compartment model for morphine and the two metabolites (M3G, M6G). The estimates (standardized to 70 kg) were: central volume of distribution (V1)= 104 L (34%), formation clearance to M3G (CL3M) = 81.8 L/h (26%), M3G volume of distribution (V3M) = 38.4L (26%), elimination clearance of M3G (CLO3M) = 16.3 L/h (23%), formation clearance to M6G (CL6M) = 6.46 L/h (21%), M6G volume of distribution (V6M) fixed to 30 L [5], elimination clearance of M6G (CLO6M) = 5.50 L/h (23%). An IIV was included on V1 (117%), CL3M (117%), V3 (134%), CLO3M (99%) and CL6M (29%). A significant influence of creatinine concentration was found on CL3M and CLOM6. No relationship was found between clearances and genetic variants for any of the three drugs.
Conclusions: Three population PK models have been developed to describe the plasma concentration of clonidine, midazolam and morphine. These models confirm the influence of weight and age on the clearance in young children. No relationship was found between genetic variants and clearance. Further analysis will be done to investigate the relationship between concentration of clonidine as well as midazolam and sedative effect (using COMFORT-B score). These PK/PD analyses will be used to compare the two drugs and determine the optimal dose of clonidine in this population.
References:
[1] Neubert, A. et al. (2017). The CLOSED trial; CLOnidine compared with midazolam for SEDation of paediatric patients in the intensive care unit: study protocol for a multicentre randomised controlled trial. BMJ Open, 7
[2] Larsson, P. et al. (2011). Oral bioavailability of clonidine in children. Paediatr Anaesth, 21, 3:335-40.
[3] Anderson, B. et al. (2011). A maturation model for midazolam clearance. Paediatr Anaesth 21, 302–308.
[4] Knøsgaard, K. et al. (2016). Pharmacokinetic models of morphine and its metabolites in neonates: Systematic comparisons of models from the literature, and development of a new meta-model. Eur J Pharm Sci, 92:117-30
[5] Bouwmeester (2004). Developmental pharmacokinetics of morphine and its metabolites in neonates, infants and young children. Br J Anaesth, 92, 2
Reference: PAGE () Abstr 9529 [www.page-meeting.org/?abstract=9529]
Poster: Drug/Disease Modelling - Paediatrics