MétaCan
Menu
Back to cohort
Record W2082316262 · doi:10.1002/bmc.1379

Metabolic stability and determination of cytochrome P450 isoenzymes' contribution to the metabolism of medetomidine in dog liver microsomes

2009· article· en· W2082316262 on OpenAlexaff
Marie‐Claude Duhamel, Éric Troncy, Francis Beaudry

Bibliographic record

VenueBiomedical Chromatography · 2009
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsCegep de Saint HyacintheUniversité de Montréal
Fundersnot available
KeywordsMedetomidineChemistryPharmacokineticsChromatographyMicrosomePharmacologyDrug metabolismMetabolismBiochemistryEnzymeInternal medicineBlood pressureHeart rate

Abstract

fetched live from OpenAlex

Medetomidine is a potent and selective alpha2-adrenergic agonist. The activation of alpha2-adrenergic receptor mediates a variety of effects including sedation, analgesia, relief of anxiety, vasoconstriction and bradycardia. However, our main interest is the sedative effects of medetomidine when used as a premedicant prior surgery in companion animals, especially in dogs. Recently, data suggested that following intravenous infusion at six dosing regiments non-linear pharmacokinetics was observed. Major causes of non-linear pharmacokinetics are the elimination of the drug not following a simple first-order kinetics and/or the elimination half-life changing due to saturation of an enzyme system. The goal of this study was to establish the metabolic stability and determine the metabolic pathway of medetomidine in dog liver microsomes. Consequently, Michaelis-Menten parameters (V(max), K(m)), T(1/2) and CL(i) were determined. The incubations were performed in a microcentrifuge tube and containing various concentrations of medetomidine (10-5000 nM), 1 mg/mL of microsomal proteins suspended in 0.1 M phosphate buffer, pH 7.4. Microsomal suspensions were preincubated with NADPH (1 mM) for 5 min at 37 degrees C prior to fortification with medetomidine. Samples were taken at various time points for kinetic information and the initial velocity (v(i)) was determined after 10 min incubation. The reaction was stopped by the addition of an internal standard solution (100 ng/mL of dextrometorphan in acetone). Medetomidine concentrations were determined using a selective and sensitive HPLC-ESI/MS/MS method. Using non-linear regression, we determined a K(m) value of 577 nM, indicating relatively low threshold enzyme saturation consistent with previous in vivo observation. The metabolic stability was determined at a concentration of 100 nm (<<K(m)) and the observed T(1/2) was 90 min with a CL(i) of 0.008 mL/min indicating moderately low clearance in dog liver microsomes, also consistent with previous in vivo data. Moreover, results suggest that principally medetomidine is metabolized by the CYP3A with a small contribution from CYP2D and CYP2E. The participation of CYP3A is an important discovery since medetomidine is used as a premedicant in combination with fentanyl, ketamine and/or midazolam. These findings combined with a low K(m) value may indicate that medetomidine can competitively inhibit the metabolism of these drugs and consequently significantly impair metabolic clearance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.309
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueBiomedical ChromatographySame topicVeterinary Pharmacology and AnesthesiaFrench-language works237,207