CYP2D6 and CYP2C19 genotype‐based dose recommendations for antidepressants: a first step towards subpopulation‐specific dosages
Bibliographic record
Abstract
OBJECTIVE: This review aimed to provide distinct dose recommendations for antidepressants based on the genotypes of cytochrome P450 enzymes CYP2D6 and CYP2C19. This approach may be a useful complementation to clinical monitoring and therapeutic drug monitoring. METHOD: Our literature search covered 32 antidepressants marketed in Europe, Canada, and the United States. We evaluated studies which had compared pharmacokinetic parameters of antidepressants among poor, intermediate, extensive and ultrarapid metabolizers. RESULTS: For 14 antidepressants, distinct dose recommendations for extensive, intermediate and poor metabolizers of either CYP2D6 or CYP2C19 were given. For the tricyclic antidepressants, dose reductions around 50% were generally recommended for poor metabolizers of substrates of CYP2D6 or CYP2C19, whereas differences were smaller for the selective serotonin reuptake inhibitors. CONCLUSION: We have provided preliminary average dose suggestions based on the phenotype or genotype. This is a first attempt to apply the new pharmacogenetics to suggest dose-regimens that take the differences in drug metabolic capacity into account.
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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 | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".