The Effects of Desvenlafaxine and Paroxetine on the Pharmacokinetics of the Cytochrome P450 2D6 Substrate Desipramine in Healthy Adults
Bibliographic record
Abstract
The potential for cytochrome P450 (CYP) 2D6 substrates to interact with desvenlafaxine (administered as desvenlafaxine succinate) and paroxetine was evaluated. In an open-label, crossover study, 20 healthy volunteers (aged 21-50) were randomized to 2 series of 9 days each of desvenlafaxine (100 mg/d) or paroxetine (20 mg/d), separated by a 5-day washout. The CYP2D6 substrate desipramine (50 mg) was administered alone on day 1 and coadministered on day 6 of dosing with either desvenlafaxine or paroxetine. CYP2D6 genotype was determined at baseline. Based on least squares geometric mean ratios between reference (desipramine alone) and test treatments, desvenlafaxine produced minor increases in desipramine area under the plasma concentration versus time curve (AUC; 36%) and peak plasma concentration (C(max); 30%) (vs paroxetine: 419%, 90%, respectively; both P < .001). Desvenlafaxine produced little change in 2-hydroxydesipramine AUC (16% increase) and C(max) (0%) versus paroxetine (18% and 82% decreases, respectively; P = .008, P < .001, respectively), indicating that desvenlafaxine, especially at the recommended therapeutic dose of 50 mg/d for major depressive disorder in the United States, has little potential to interact with CYP2D6 substrates.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".