Pharmacokinetics and pharmacodynamics of intravenous dexmedetomidine in healthy Korean subjects. 2012

S Lee, and B-H Kim, and K Lim, and D Stalker, and W Wisemandle, and S-G Shin, and I-J Jang, and K-S Yu
Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Korea.

OBJECTIVE Dexmedetomidine is a selective alpha2-adrenoreceptor agonist used for sedation in critically ill patients. The current study aimed to evaluate the pharmacokinetics (PKs), pharmacodynamics and tolerability of intravenous dexmedetomidine in healthy Korean subjects. METHODS A randomized, double-blind, placebo-controlled study with three parallel dosage groups was conducted. Twenty-four subjects were randomly assigned to placebo or one of three dexmedetomidine dosing regimens, 3 μg/kg/h for 10 min followed by 0.17 μg/kg/h for 50 min (low dose), 6 μg/kg/h for 10 min followed by 0.34 μg/kg/h for 50 min (middle dose) and 3.7 μg/kg/h for 35 min followed by 0.7 μg/kg/h for 25 min (high dose). Serial blood samples for PK analysis were taken up to 12 h. PK parameters were determined using non-compartmental methods (WinNonlin(®)), and a population PK model was developed using nonmem(®). The sedative effect of dexmedetomidine was assessed by Ramsay sedation score and visual analogue scales/sedation. Adverse events, clinical laboratory tests, electrocardiograms, physical examinations and vital signs were monitored for tolerability assessment. RESULTS Six subjects were assigned to each of the three active treatment group or placebo group. The AUC(last) of the low-, middle- and high-dose group were 1096.8 ± 119.9 (mean ± SD) ng*h/L, 2643.0 ± 353.2 ng*h/L and 5600.6 ± 411.0 ng*h/L, respectively. PK of dexmedetomidine was best described using a two-compartment model. The typical value of the population model can be calculated using the following equations: central volume of distribution (L) = 19.9 (age/27)(0.954), peripheral volume of distribution (L) = 59.4, clearance (L/h) = 33.7 (albumin level/4.3)(1.42) and inter-compartment clearance (L/h) = 67.7. Sedative effects were significantly increased by dexmedetomidine compared to placebo. The blood pressure and heart rate were decreased, but oxygen saturation was maintained stable. CONCLUSIONS Dexmedetomidine shows linear PK characteristics and dose-dependent sedative effects. A two-compartment population PK model was developed for healthy Korean subjects. The PK parameter estimates are similar in Koreans and Caucasians.

UI MeSH Term Description Entries
D006993 Hypnotics and Sedatives Drugs used to induce drowsiness or sleep or to reduce psychological excitement or anxiety. Hypnotic,Sedative,Sedative and Hypnotic,Sedatives,Hypnotic Effect,Hypnotic Effects,Hypnotics,Sedative Effect,Sedative Effects,Sedatives and Hypnotics,Effect, Hypnotic,Effect, Sedative,Effects, Hypnotic,Effects, Sedative,Hypnotic and Sedative
D007262 Infusions, Intravenous The long-term (minutes to hours) administration of a fluid into the vein through venipuncture, either by letting the fluid flow by gravity or by pumping it. Drip Infusions,Intravenous Drip,Intravenous Infusions,Drip Infusion,Drip, Intravenous,Infusion, Drip,Infusion, Intravenous,Infusions, Drip,Intravenous Infusion
D008297 Male Males
D008954 Models, Biological Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment. Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D004305 Dose-Response Relationship, Drug The relationship between the dose of an administered drug and the response of the organism to the drug. Dose Response Relationship, Drug,Dose-Response Relationships, Drug,Drug Dose-Response Relationship,Drug Dose-Response Relationships,Relationship, Drug Dose-Response,Relationships, Drug Dose-Response
D004311 Double-Blind Method A method of studying a drug or procedure in which both the subjects and investigators are kept unaware of who is actually getting which specific treatment. Double-Masked Study,Double-Blind Study,Double-Masked Method,Double Blind Method,Double Blind Study,Double Masked Method,Double Masked Study,Double-Blind Methods,Double-Blind Studies,Double-Masked Methods,Double-Masked Studies,Method, Double-Blind,Method, Double-Masked,Methods, Double-Blind,Methods, Double-Masked,Studies, Double-Blind,Studies, Double-Masked,Study, Double-Blind,Study, Double-Masked
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D014018 Tissue Distribution Accumulation of a drug or chemical substance in various organs (including those not relevant to its pharmacologic or therapeutic action). This distribution depends on the blood flow or perfusion rate of the organ, the ability of the drug to penetrate organ membranes, tissue specificity, protein binding. The distribution is usually expressed as tissue to plasma ratios. Distribution, Tissue,Distributions, Tissue,Tissue Distributions
D017711 Nonlinear Dynamics The study of systems which respond disproportionately (nonlinearly) to initial conditions or perturbing stimuli. Nonlinear systems may exhibit "chaos" which is classically characterized as sensitive dependence on initial conditions. Chaotic systems, while distinguished from more ordered periodic systems, are not random. When their behavior over time is appropriately displayed (in "phase space"), constraints are evident which are described by "strange attractors". Phase space representations of chaotic systems, or strange attractors, usually reveal fractal (FRACTALS) self-similarity across time scales. Natural, including biological, systems often display nonlinear dynamics and chaos. Chaos Theory,Models, Nonlinear,Non-linear Dynamics,Non-linear Models,Chaos Theories,Dynamics, Non-linear,Dynamics, Nonlinear,Model, Non-linear,Model, Nonlinear,Models, Non-linear,Non linear Dynamics,Non linear Models,Non-linear Dynamic,Non-linear Model,Nonlinear Dynamic,Nonlinear Model,Nonlinear Models,Theories, Chaos,Theory, Chaos

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