Effect of Desvenlafaxine on the Cytochrome P450 2D6 Enzyme System
Bibliographic record
Abstract
BACKGROUND: The cytochrome P450 2D6 (CYP2D6) enzyme is responsible for metabolizing approximately 25% of pharmaceutical agents. Individuals with impaired CYP2D6 metabolism and those concomitantly receiving agents that inhibit CYP2D6 can have variations in concentrations of such medications and their metabolites. METHODS: Five studies assessing the interaction between desvenlafaxine and CYP2D6 are reviewed. Study 1 compared desvenlafaxine area under the plasma concentration-versus-time curve (AUC) in CYP2D6 extensive metabolizers (EMs) and poor metabolizers (PMs) after administration of 100 mg of desvenlafaxine or 75 mg of venlafaxine extended release (ER). Studies 2 to 5 assessed the effect of concomitant administration of desvenlafaxine 100 mg (studies 2, 4, and 5) or 400 mg (study 3), paroxetine (20 mg, study 4), and duloxetine (30 mg twice daily; study 5) on the CYP2D6 probe desipramine. RESULTS: In study 1, there was no significant difference in mean desvenlafaxine AUC between the CYP2D6 EMs and PMs (-11%; P=0.641) who were administered desvenlafaxine. However, PMs receiving venlafaxine ER had significantly higher venlafaxine and lower desvenlafaxine AUCs compared with EMs (+350% and -74%, respectively; P<0.001 for each). In studies 2, 4, and 5, the mean increases in desipramine AUC with concomitant administration of desvenlafaxine 100 mg ranged from 17% to 36%; the increase with concomitant administration of desvenlafaxine 400 mg (study 3) was 90%. Paroxetine and duloxetine produced increases in mean desipramine AUC of 419% and 122%, respectively, which were significantly greater than the increases seen with desvenlafaxine 100 mg (P<0.001 for each comparison). CONCLUSIONS: Based on the findings presented here, desvenlafaxine is expected to have a low risk for variability in efficacy and safety/tolerability resulting from CYP2D6 polymorphisms or drug-drug interactions when coadministered with CYP2D6 substrates or inhibitors.
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 | 0.001 |
| 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) | 0.002 | 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".