Effect of verapamil on systemic exposure and safety of umeclidinium and vilanterol: a randomized and open-label study
Bibliographic record
Abstract
BACKGROUND: The combination of umeclidinium (UMEC), a long-acting muscarinic receptor antagonist, and vilanterol (VI), a selective long-acting β₂ agonist, is in development for the treatment of chronic obstructive pulmonary disease (COPD). This study evaluated the pharmacokinetics, safety and tolerability, and pharmacodynamics of once-daily, inhaled UMEC and UMEC/VI when co-administered with oral verapamil, a moderate P-glycoprotein transporter and moderate cytochrome P450 3A4 (CYP3A4) inhibitor frequently used by patients with COPD and cardiovascular comorbidities. METHODS: Subjects were randomized to one of two 13-day treatment regimens: UMEC 500 μg or UMEC 500 μg/VI 25 μg. All subjects received a single tablet containing 240 mg verapamil on each of days 9-13. RESULTS: Repeat doses of UMEC and UMEC/VI in combination with and without verapamil were safe and well tolerated. There was no increase in systemic exposure of UMEC when administered in combination with VI compared to UMEC alone. UMEC maximum concentration was similar with or without verapamil; a moderate increase in UMEC area under the curve (approximately 1.4-fold) was observed with verapamil. Verapamil did not increase systemic exposure to VI following administration of the UMEC/VI combination. CONCLUSION: Administration of UMEC and UMEC/VI combination was well tolerated and did not show clinically relevant increases in systemic exposure for either drug. The UMEC/VI combination is unlikely to have a clinically meaningful drug-drug interaction with moderate P-glycoprotein transporter and CYP3A4 inhibitor drugs.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".