Multiple Doses of Rifabutin Reduce Exposure of Doravirine in Healthy Subjects
Bibliographic record
Abstract
Doravirine is a nonnucleoside reverse transcriptase inhibitor in clinical development for the treatment of human immunodeficiency virus-1 infection in combination with other antiretroviral therapies. The cytochrome P450 (CYP)3A-dependent metabolism of doravirine makes it susceptible to interactions with modulators of this pathway, including the antituberculosis treatment rifampin. Rifabutin, an alternative antibiotic used to treat tuberculosis, may have a lower-magnitude effect on CYP3A. The aim of this trial was to determine the effect of steady-state rifabutin on doravirine single-dose pharmacokinetics and tolerability. In this open-label, 2-period, fixed-sequence, drug-drug interaction study, healthy subjects received a single dose of doravirine 100 mg alone and coadministered on day 14 of once-daily administration of rifabutin 300 mg for 16 days. Plasma samples were taken to determine doravirine pharmacokinetics, and safety was monitored throughout. Dose adjustment of doravirine in the presence of coadministered rifabutin was explored through nonparametric superposition analysis. Rifabutin reduced doravirine area under the concentration-time curve from time zero to infinite and plasma drug concentration 24 hours postdose with geometric mean ratios ([rifabutin+doravirine]/[doravirine alone]) (90%CIs) of 0.50 (0.45-0.55) and 0.32 (0.28-0.35), respectively. Doravirine apparent clearance increased from 5.9 L/h without rifabutin to 12.2 L/h when coadministered. Doravirine pharmacokinetics with and without coadministered rifabutin were not equivalent. Nonparametric superposition analysis projected that administration of doravirine 100 mg twice daily with rifabutin will restore steady-state trough concentration values to efficacious levels associated with doravirine 100 mg once daily in the absence of CYP3A inducers. Doravirine may be coadministered with rifabutin when the doravirine dose frequency is increased from 100 mg once daily to 100 mg twice daily.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".