Metabolism of Atypical Antipsychotics: Involvement of Cytochrome P450 Enzymes and Relevance for Drug-Drug Interactions
Bibliographic record
Abstract
The involvement of cytochrome P450 (CYP) enzymes in the metabolism of the atypical (second-generation) antipsychotics clozapine, risperidone, olanzapine, quetiapine, ziprasidone, aripiprazole, paliperidone and amisulpride is reviewed, and the possible relevance of this metabolism to drug-drug interactions is discussed. Clozapine is metabolized primarily by CYP1A2, with additional contributions by CYP2C19, CYP2D6 and CYP3A4. Risperidone is metabolized primarily by CYP2D6 and to a lesser extent by CYP3A4; the 9-hydroxy metabolite of risperidone (paliperidone) is now marketed as an antipsychotic in its own right. Olanzapine is metabolized primarily by direct glucuronidation and CYP1A2 and to a lesser extent by CYP2D6 and CYP3A4. Quetiapine is metabolized by CYP3A4, as is ziprasidone, although in the latter case aldehyde oxidase is the enzyme responsible for most of the metabolism. CYP2D6 and CYP3A4 are important in the metabolism of aripiprazole, and CYP-catalyzed metabolism of paliperidone and amisulpride appears to be minor. At the usual clinical doses, these drugs appear to not generally affect markedly the metabolism of other coadministered medications. However, as indicated above, several of atypical antipsychotics are metabolized by CYP enzymes, and physicians should be aware of coadministered drugs that may inhibit or induce these CYP enzymes; examples of such possible interactions are presented in this review.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".