Population Pharmacokinetics of Vernakalant Hydrochloride Injection (RSD1235) in Patients With Atrial Fibrillation or Atrial Flutter
Bibliographic record
Abstract
Vernakalant hydrochloride is a novel, predominantly atrial-selective antiarrhythmic drug that effectively and rapidly terminates atrial fibrillation (AF). Plasma vernakalant concentration data from 5 phase 2 and 3 clinical trials of vernakalant in patients with AF or atrial flutter and a phase 1 study in healthy volunteers were used to construct a population pharmacokinetic model. Plasma vernakalant concentration-time data were best fit by a 2-compartment mammillary model, with rapid first-order elimination from the central compartment. Median systemic clearance was 0.35 L/h/kg (or 28 L/h for an 80-kg patient), with intersubject variability estimated to be 40%. Clearance was significantly influenced by CYP2D6 genotype, age, serum creatinine concentration, and subject status (patient vs volunteer). The intercompartmental clearance was also influenced by subject status, whereas the volumes of the central compartment and peripheral compartment were unaffected by any covariates. Based on the final pharmacokinetic model, the area under the plasma vernakalant concentration-time curve from 0 to 90 minutes was estimated to be 15% higher in CYP2D6 poor metabolizers than extensive metabolizers, with age and serum creatinine having much smaller influences on exposure. These data suggest that dose adjustments based on patient characteristics, including use of concomitant drugs, are unnecessary for intravenous vernakalant.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".