Pharmacokinetic interaction between single oral doses of ditiazem and sirolimus in healthy volunteers*1
Bibliographic record
Abstract
AIM AND BACKGROUND: The pharmacokinetic interaction between sirolimus, a macrolide immunosuppressant metabolized by CYP3A4, and the calcium channel blocker diltiazem was studied in 18 healthy subjects. Several clinically important interactions have previously been reported for other immunosuppressive drugs that are metabolized by the same enzyme and for calcium antagonists. METHODS: Healthy subjects who were 20 to 43 years old participated in an open, three-period, randomized, crossover study of the pharmacokinetics of a single 10-mg oral dose of sirolimus, a single oral 120-mg dose of diltiazem, and the two drugs given together. The three study periods were separated by a 21-day washout phase. RESULTS: The geometric mean (90% confidence interval) whole blood sirolimus area under the plasma concentration time-curve increased 60% (35%-90%), from 736 to 1178 ng x h/mL, and maximum concentration increased 43% (14%-81%), from 67 to 96 ng/mL, with diltiazem coadministration, whereas the mean elimination half-life of sirolimus decreased slightly, from 79 to 67 hours. Apparent oral clearance and volume of distribution of sirolimus decreased with 38% and 45%, respectively, when sirolimus was given with diltiazem. The plasma maximum concentration and area under the plasma concentration-time curve of diltiazem, desacetyldiltiazem, and desmethyldiltiazem were unchanged after coadministration of sirolimus, and no potentiation of the effects of diltiazem on diastolic or systolic blood pressure or on the electrocardiographic parameters was seen. CONCLUSIONS: Single-dose diltiazem coadministration leads to higher sirolimus exposure, presumably by inhibition of the first-pass metabolism of sirolimus. Because of the pronounced intersubject variability in the extent of the sirolimus-diltiazem interaction, whole blood sirolimus concentrations should be monitored closely in patients treated with the two drugs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".