Clozapine Exposure and the Impact of Smoking and Gender: A Population Pharmacokinetic Study
Bibliographic record
Abstract
The primary objective of this study was to evaluate the magnitude and variability of concentration exposure to clozapine and norclozapine in a real-world clinical setting, with a focus on smoking status, using population pharmacokinetic methodologies. A retrospective review of plasma clozapine and norclozapine concentrations taken from inpatients at the Centre for Addiction and Mental Health, Toronto, from 2001 to 2007 was conducted. A nonlinear mixed-effects model was developed using NONMEM, including age, gender, weight, smoking status, and dosage formulation as covariates. Pharmacokinetic parameters and interindividual and residual variabilities were estimated with 1- and 2-compartment models. A total of 519 plasma clozapine concentrations from 197 patients (138 males; mean +/- SD age, 38 +/- 13 years; schizophrenia spectrum disorder 98.2%) were included for the analysis. A 1-compartment model with first-order absorption and elimination best described the data. Apparent volume of distribution was fixed to a previously reported value in the literature of 7 L/kg.The population-predicted oral clearance of clozapine and norclozapine was 18.0 and 39.0 L/h, respectively; both the predicted clearance values vary nearly 6-fold (range, 9.18-59.06 and 16.29-97.84 L/h, respectively). For clozapine, smokers and males showed increased oral clearance by 6.0 and 4.5 L/h, respectively. For norclozapine, smokers and male gender were associated with an increased oral clearance of 11.3 and 7.6 L/h, respectively. The formulation of clozapine administered had an impact on the absorption rate with a Ka of 0.14/h for tablet and 10.3/h for the suspension form.The data suggest that smoking and male gender are associated with lower exposure to clozapine and norclozapine due to the higher oral clearance. These findings may account for some of the variability in clozapine exposure and have important implications for individualized drug dosing and therapeutic drug monitoring.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".