Investigation of a Potential Pharmacokinetic Interaction Between Nebivolol and Fluvoxamine in Healthy Volunteers
Bibliographic record
Abstract
PURPOSE: To investigate whether fluvoxamine coadministration can influence the pharmacokinetic properties of nebivolol and its active hydroxylated metabolite (4-OH-nebivolol) and to assess the consequences of this potential pharmacokinetic interaction upon nebivolol pharmacodynamics. METHODS: This open-label, non-randomized, sequential clinical trial consisted of two periods: Period 1 (Reference), during which each volunteer received a single dose of 5 mg nebivolol and Period 2 (Test), when a combination of 5 mg nebivolol and 100 mg fluvoxamine was given to all subjects, after a 6-days pretreatment regimen with fluvoxamine (50-100 mg/day). Non-compartmental analysis was used to determine the pharmacokinetic parameters of nebivolol and its active metabolite. The pharmacodynamic parameters (blood pressure and heart rate) were assessed at rest after each nebivolol intake, during both study periods. RESULTS: Fluvoxamine pretreatment increased Cmax and AUC0-∞ of nebivolol (Cmax: 1.67 ± 0.690 vs 2.20 ± 0.970 ng/mL; AUC0-∞: 12.1 ± 11.0 vs 19.3 ± 19.5 ng*h/mL ) and of its active metabolite (Cmax: 0.680 ± 0.220 vs 0.960 ± 0.290 ng/mL; AUC0-∞: 17.6 ±20.1 vs 25.5 ± 29.9 ng*h/mL). Apart from Cmax,AUC0-t and AUC0-∞, the other pharmacokinetic parameters (tmax, kel and t½) were not significantly different between study periods. As for the pharmacodynamic analysis, decreases in blood pressure and heart rate after nebivolol administration were similar with and without fluvoxamine concomitant intake. CONCLUSIONS: Due to enzymatic inhibition, fluvoxamine increases the exposure to nebivolol and its active hydroxylated metabolite in healthy volunteers. This did not influence the blood pressure and heart-rate lowering effects of the beta-blocker administered as single-dose. However, more detail studies involving actual patients are required to further investigate the clinical relevance of this drug interaction. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".