Quantitative determination of armodafinil in human plasma by liquid chromatography–electrospray mass spectrometry: Application to a clinical study
Bibliographic record
Abstract
Abstract Armodafinil is a wake‐promoting agent approved in 2007 by the US Food and Drug Administration for the treatment of excessive sleepiness. A rapid, sensitive and selective liquid chromatography–tandem mass spectrometry (LC‐MS/MS) method for the determination of armodafinil in human plasma was developed and validated. Armodafinil and internal standard (armodafinil d‐10) were extracted from human plasma using protein precipitation combined with liquid–liquid extraction. This developed method only requires 50 μL of plasma for the analysis. The chromatographic separation was performed with a Waters symmetry, C 18 , 4.6 × 150 mm, 5 μm column using formic acid, water and acetonitrile as solvent delivered at a 0.7 mL/min flow rate. The total run time of the method was 3 min. The method was validated according to regulatory guidance in terms of specificity, selectivity, linearity, matrix effect, recovery and stability. Optimized Q1/Q3 mass transitions for armodafinil and armodafinil d‐10 were 274.1/167.2 ( m / z ) and 284.4/177.4 ( m / z ) respectively. The method showed linearity within the tested concentration range of 10–10,000 ng/mL. The method was successfully applied to quantify armodafinil concentrations after single oral administration of a 250 mg tablet in a clinical study conducted in healthy volunteers. Significant advantages of this method are minimal sample volume, short run time and a lower LLOQ.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".