Population Pharmacokinetic Model of Dexmedetomidine in a Heterogeneous Group of Patients

Abstract

Dexmedetomidine is a hepatically eliminated drug with sedative, anxiolytic, sympatholytic, and analgesic properties that has been increasingly used for various indications in the form of a short or continuous intravenous infusion. This study aimed to propose a population pharmacokinetic (PK) model of dexmedetomidine in a heterogeneous group of intensive care unit patients, incorporating 29 covariates potentially linked with dexmedetomidine PK. Data were collected from 70 patients aged between 0.25 and 88 years and treated with dexmedetomidine infusion for various durations at 1 of 4 medical centers. Statistical analysis was performed using a nonlinear mixed-effect model. Categorical and continuous covariates including demographic data, hemodynamic parameters, biochemical markers, and 11 single-nucleotide polymorphisms were tested. A 2-compartment model was used to describe dexmedetomidine PK. An allometric/isometric scaling was used to account for body weight difference in PK parameters, and the Hill equation was used to describe the maturation of clearance. Typical values of the central and peripheral volume of distribution and the systemic and distribution clearance for a theoretical adult patient were central volume of distribution = 22.50 L, peripheral volume of distribution = 86.1 L, systemic clearance = 34.7 L/h, and distribution clearance = 40.8 L/h. The CYP1A2 genetic polymorphism and noradrenaline administration were identified as significant covariates for clearance. A population PK model of dexmedetomidine was successfully developed. The proposed model is well calibrated to the observed data. The identified covariates account for <5% of interindividual variability and consequently are of low clinical significance for the purpose of dose adjustment.

Population Pharmacokinetic Analysis of Dexmedetomidine in Children using Real World Data from Electronic Health Records and Remnant Specimens

“…Following this we considered size and age maturation; these two covariates have been shown to be important factors in pediatric PK models with a large age range and in previous dexmedetomidine studies. 6,8,16,17,[37][38][39] For size, we employed an allometric weight model with fixed or estimated scaling parameters. For maturation, we considered an exponential age model, a sigmoid Hill maturation model, a bodyweight dependent exponent model, and an age-dependent exponent model.…”

“…Importantly, population PK models can identify covariates that affect each individual's PK profile, facilitating personalized dosing. Several population PK studies of dexmedetomidine in pediatric populations have been reported, [5][6][7][8][9][10][11][12][13][14][15][16][17] often using a small number of individuals and frequent sample collection [median sample size 29, range 18-199 for pediatric ICU populations]. 7,[9][10][11][12]14,15 Strategies to address small sample size include pooled pediatric analyses, 17 creating "universal" models for both children and adults, 6,8 and Bayesian analyses with informative priors; 16 however, even these models only include information from at most around 130 children.…”

“…For pediatric ICU populations, the median sample size is 29.5 (range , and the median number of total drug levels collected is 236.5 (range 89 -1967) with a median of 9 per subject (range 2 -16). 5,7,[9][10][11][12]14,15 Some studies have addressed small sample size with methods that combine information from multiple populations including pooled pediatric analyses, 17 creating "universal" models for children and adults, 6,8 and Bayesian analyses with informative priors; 16 however, even these models only include information from at most around 130 children.…”

“…Many population pharmacokinetic (PK) studies of dexmedetomidine in pediatric populations have been reported. [5][6][7][8][9][10][11][12][13][14][15][16][17] For example, Potts et al 17 report on dexmedetomidine use in 95 pediatric ICU patients using data pooled from several previous studies, Su et al 15 studied 59 children on mechanical ventilation after open heart surgery, Pérez-Guillé et al 12 assessed 30 children undergoing ambulatory surgery, and Zuppa et al 9 examined dexmedetomidine PK among 119 children undergoing cardiac surgery. Most have a small number of individuals and frequent specimen collection.…”

“…Previously, studies have identified weight [5][6][7][8][9][10][11][12][14][15][16][17] and age 5,6,[8][9][10][14][15][16][17] , along with cardiac bypass 9,10,15 , as important factors to explain inter-individual variability. However, lower sample size may limit identification of additional covariates impacting inter-individual variability.…”