The Role of Cytochrome P450 2C19 Activity in Flunitrazepam Metabolism In Vivo
Bibliographic record
Abstract
Flunitrazepam, a hypnotic benzodiazepine, is widely prescribed around the world for the treatment of insomnia and as a preanesthetic. In vitro studies have shown that the metabolism of flunitrazepam to desmethylflunitrazepam and 3-hydroxyflunitrazepam is mediated in part by the polymorphic enzyme CYP2C19. The objective was to examine the role of CYP2C19 activity in determining flunitrazepam kinetics in vivo. Sixteen healthy volunteers (14 genotypic extensive metabolizers and 2 poor metabolizers) were recruited who had a wide range of CYP2C19 activity (0.50-28.8), as determined by the omeprazole/ 5-hydroxyomeprazole ratio (OMR) at 3 hours following administration of omeprazole, 20 mg orally. Each subject received flunitrazepam, 1 mg orally. Blood samples were collected immediately before and up to 48 hours after drug administration and were assayed by HPLC for flunitrazepam and its metabolites, 7-aminoflunitrazepam, desmethylflunitrazepam, and 3-hydroxyflunitrazepam. Spearman correlations were determined for OMR and pharmacokinetic parameters. With increasing OMR (decreasing CYP2C19 activity), the ratio of flunitrazepam to both desmethylflunitrazepam and 3-hydroxyflunitrazepam AUCs increased ( r = 0.55, p = 0.03 and r = 0.65, p = 0.01, respectively). However, variation in CYP2C19 activity did not significantly affect the AUCs of flunitrazepam or its metabolites. The authors conclude that CYP2C19 contributes to the metabolism of flunitrazepam to desmethylflunitrazepam and 3-hydroxyflunitrazepam in vivo, but these data suggest that its role is minor and that differences in CYP2C19 activity do not likely substantially influence its clinical effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".