Population pharmacokinetic analysis of dexmedetomidine in children using real‐world data from electronic health records and remnant specimens. Issue 6 (28th January 2022) - James, Nathan T.; Breeyear, Joseph H.; Caprioli, Richard; Edwards, Todd; Hachey, Brian; Kannankeril, Prince J.; Keaton, Jacob M.; Marshall, Matthew D.; Van Driest, Sara L.; Choi, Leena
Abstract : Aims: Our objectives were to perform a population pharmacokinetic analysis of dexmedetomidine in children using remnant specimens and electronic health records (EHRs) and explore the impact of patient's characteristics and pharmacogenetics on dexmedetomidine clearance. Methods: Dexmedetomidine dosing and patient data were gathered from EHRs and combined with opportunistically sampled remnant specimens. Population pharmacokinetic models were developed using nonlinear mixed‐effects modelling. Stage 1 developed a model without genotype variables; Stage 2 added pharmacogenetic effects. Results: Our final study population included 354 post‐cardiac surgery patients aged 0–22 years (median 16 mo). The data were best described with a 2‐compartment model with allometric scaling for weight and Hill maturation function for age. Population parameter estimates and 95% confidence intervals were 27.3 L/h (24.0–31.1 L/h) for total clearance, 161 L (139–187 L) for central compartment volume of distribution, 26.0 L/h (22.5–30.0 L/h) for intercompartmental clearance and 7903 L (5617–11 119 L) for peripheral compartment volume of distribution. The estimate for postmenstrual age when 50% of adult clearance is achieved was 42.0 weeks (41.5–42.5 weeks) and the Hill coefficient estimate was 7.04 (6.99–7.08). Genotype was not statistically or clinically significant. Conclusion: Our study demonstrates the use of real‐world EHR data and remnant specimens to perform a population pharmacokinetic analysis and investigate covariate effects in a large paediatric population. Weight and age were important predictors of clearance. We did not find evidence for pharmacogenetic effects of UGT1A4 or UGT2B10 genotype or CYP2A6 risk score.