Clinical Pharmacogenetics Implementation Consortium Guideline for <i>CYP2B6</i> Genotype and Methadone Therapy
Bibliographic record
Abstract
Methadone is a mu (μ) opioid receptor agonist used clinically in adults and children to manage opioid use disorder, neonatal abstinence syndrome, and acute and chronic pain. It is typically marketed as a racemic mixture of R- and S-enantiomers. R-methadone has 30-to 50-fold higher analgesic potency than S-methadone, and S-methadone has a greater adverse effect (prolongation) on the cardiac QTc interval. Methadone undergoes stereoselective metabolism. CYP2B6 is the primary enzyme responsible for catalyzing the metabolism of both enantiomers to the inactive metabolites, S- and R-2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (S- and R-EDDP). Genetic variation in the CYP2B6 gene has been investigated in the context of implications for methadone pharmacokinetics, dose, and clinical outcomes. Most CYP2B6 variants result in diminished or loss of CYP2B6 enzyme activity, which can lead to higher plasma methadone concentrations (affecting S- more than R-methadone). However, the data do not consistently indicate that CYP2B6-based metabolic variability has a clinically significant effect on methadone dose, efficacy, or QTc prolongation. Expert analysis of the published literature does not support a change from standard methadone prescribing based on CYP2B6 genotype (updates at www.cpicpgx.org).
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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 | 0.022 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.024 | 0.020 |
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".