Red wine decreases cyclosporine bioavailability
Bibliographic record
Abstract
Background Many commonly ingested substances such as grapefruit juice and Hypericum perforatum (St John's wort) have been found to interact with important therapeutic agents such as cyclosporine (INN, ciclosporin). The mechanism for these interactions is thought to involve modulation of the activity of the drug‐metabolizing enzyme cytochrome P4503A4 (CYP3A4) and/or the drug transport protein P‐glycoprotein. In vitro data suggest that red wine may interact with CYP3A4 substrates such as cyclosporine. Methods We conducted a randomized, 2‐way crossover study of 12 healthy individuals. Subjects received a single 8‐mg/kg dose of oral cyclosporine with water (control) and with 12 oz of red wine (Blackstone Merlot 1996; Blackstone Winery, Graton, Calif). Whole blood was analyzed for cyclosporine and 6 metabolites by specific fluorescence polarization immunoassay and tandem liquid chromatography‐mass spectrometry. Blood levels of cyclosporine were compared between the 2 arms. Results Red wine caused a 50% increase in the oral clearance of cyclosporine. Systemic exposure as measured by the area under the concentration‐versus‐time curve (AUC) and peak concentration (C max ) were significantly decreased by red wine. However, half‐life was not affected, suggesting that red wine decreased cyclosporine absorption. In vitro, the solubility of cyclosporine in red wine appeared to be lower than in water. Conclusions Administration of cyclosporine with red wine causes a significant decrease in cyclosporine exposure. Because cyclosporine is a narrow therapeutic range compound, caution may be warranted with concomitant intake of red wine and cyclosporine. Clinical Pharmacology & Therapeutics (2001) 70 , 462–467; doi: 10.1016/S0009‐9236(01)70992‐7
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".