Effect of Steady‐State Faldaprevir on Pharmacokinetics of Atorvastatin or Rosuvastatin in Healthy Volunteers: A Prospective Open‐Label, Fixed‐Sequence Crossover Study
Bibliographic record
Abstract
Abstract Faldaprevir (FDV) is a potent, orally administered inhibitor of hepatitis C virus protease. It inhibits multiple cytochrome P‐450 enzymes and multiple membrane transporters. The objective of this study was to evaluate the effect of steady‐state faldaprevir on the pharmacokinetics (PK) of a single dose of atorvastatin or rosuvastatin. In this single‐center, open‐label, fixed‐sequence crossover study, 33 healthy adult male and female volunteers were given either atorvastatin 10 mg (n = 16) or rosuvastatin 10 mg (n = 17) on day 1. Subjects subsequently received 240 mg twice daily of faldaprevir (loading dose) on day 5, followed by 240 mg faldaprevir once daily from day 6 to day 10, with an additional single dose of atorvastatin (10 mg) or rosuvastatin (10 mg) given on day 10. PK samples for the statins were collected on days 1–3 and days 10–12. Concomitant administration with faldaprevir led to approximately 9‐fold and 34‐fold increases in AUC0–∞ and Cmax, respectively, of atorvastatin and approximately 15‐fold and 33‐fold increases in AUC0–∞ and Cmax, respectively, of rosuvastatin, compared with the statins given alone. Exposure to the major metabolites (ortho‐hydroxyatorvastatin and N‐desmethylrosuvastatin) was increased to a similar magnitude as that of the parent compounds. The marked drug–drug interaction observed is most likely related to the inhibitory effects of faldaprevir on transporters, particularly hepatic uptake transporters such as OTAP1B1 and OATP1B3. Given the significant increase in exposure to statins in healthy volunteers, coadministration of faldaprevir with statins should be avoided.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".