Population Pharmacokinetic Model of Dexmedetomidine in a Heterogeneous Group of Patients

Genetic polymorphisms are associated with individual susceptibility to dexmedetomidine

Introduction: Dexmedetomidine (DXM) is widely used as an adjuvant to anesthesia or a sedative medicine, and differences in individual sensitivity to the drug exist. This study aimed to investigate the effect of genetic polymorphisms on these differences. Methods: A total of 112 patients undergoing hand surgery were recruited. DXM 0.5 μg/kg was administered within 10 min and then continuously injected (0.4 μg/kg/h). Narcotrend index, effective dose and onset time of sedation, MAP, and HR were measured. Forty-five single nucleotide polymorphisms (SNPs) were selected for genotype. Results: We observed individual differences in the sedation and hemodynamics induced by DXM. ABCG2 rs2231142, CYP2D6 rs16947, WBP2NL rs5758550, KATP rs141294036, KCNMB1 rs11739136, KCNMA1 rs16934182, ABCC9 rs11046209, ADRA2A rs1800544, and ADRB2 rs1042713 were shown to cause statistically significant (p < 0.05) influence on the individual variation of DXM on sedation and hemodynamics. Moreover, the multiple linear regression analysis indicated sex, BMI, and ADRA2A rs1800544 are statistically related to the effective dose of DXM sedation. Discussion: The evidence suggests that the nine SNPs involved in transport proteins, metabolic enzymes, and target proteins of DXM could explain the individual variability in the sedative and hemodynamic effects of DXM. Therefore, with SNP genotyping, these results could guide personalized medication and promote clinical and surgical management.

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

AIM

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 modeling. Stage one developed a model without genotype variables; Stage two added pharmacogenetic effects.

RESULTS

Our final study population included 354 post-cardiac surgery patients age 0 to 22 years (median 16 months). The data were best described with a two-compartment model with allometric scaling for weight and Hill maturation function for age. Population parameter estimates and 95% confidence intervals were 27.3 L/hr (24.0 - 31.1 L/hr) for total clearance (CL), 161 L (139 - 187 L) for central compartment volume of distribution (V₁ ), 26.0 L/hr (22.5 - 30.0 L/hr) for intercompartmental clearance (Q), and 7903 L (5617 - 11119 L) for peripheral compartment volume of distribution (V₂ ). 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 PK analysis and investigate covariate effects in a large pediatric 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.