Development and validation of a sensitive LC‐MS/MS‐ESI method for the determination of ivabradine in human plasma: application to a pharmacokinetic study
Bibliographic record
Abstract
A sensitive, rapid assay method for estimating ivabradine in human plasma has been developed and validated using liquid chromatography coupled to tandem mass spectrometry with electrospray ionization in the positive-ion mode. The procedure involved extraction of ivabradine and the internal standard (IS) from human plasma by solid-phase extraction. Chromatographic separation was achieved using an isocratic mobile phase (0.1% formic acid-methanol, 60:40, v/v) at a flow rate of 1.0 mL/min on an Aglient Eclipse XDB C8 column (150 × 4.6 mm, 5 µm; maintained at 35 °C) with a total run time of 4.5 min. Detection was achieved using an Applied Biosystems MDS Sciex (Concord, Ontario, Canada) API 3200 triple-quadrupole mass spectrometer. The MS/MS ion transitions monitored were 469-177 for ivabradine and 453-177 for IS. Method validation was performed according to Food and Drug Administration guidelines, and the results met the acceptance criteria. The calibration curve was linear over a concentration range of 0.1-200 ng/mL. The lower limit of quantitation achieved was 0.1 ng/mL. Intra- and inter-day precisions were in the range of 1.23-14.17% and 5.26-8.96%, respectively. Finally, the method was successfully used in a pharmacokinetic study that measured ivabradine levels in healthy volunteers after a single 5 mg oral dose of ivabradine. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".