Prediction of Hepatic Clearance of Stereoselective Metabolism of Carvedilol in Liver Microsomes and Hepatocytes of Sprague-Dawley and Cytochrome P450 2D-Deficient Dark Agouti Rats
Bibliographic record
Abstract
Hepatic clearance (CLh) of carvedilol (CAR), which is eliminated via stereoselective metabolism by the CYP2D subfamily of cytochromes P450 (CYPs), was predicted using liver microsomes and hepatocytes from Sprague-Dawley (SD) rats and CYP2D-deficient Dark Agouti (DA) rats to determine the usefulness of prediction method. Plasma concentrations of CAR following intravenous injection to DA rats were higher than those in SD rats. The volume of distribution at steady state and total clearance (CLtot) of S-CAR were approximately two times greater than those of R-CAR in both strains. CLh predicted from in vitro studies using DA rat liver microsomes was different from that obtained from in vivo studies. In contrast, in vitro CLh prediction using DA rat hepatocytes was nearly identical to the CLh observed in DA rats in vivo, and was lower than that in SD rats. The predicted CLh in vitro using hepatocytes correlated well with the observed CLtot in vivo, which is expected to be nearly the same as CLh. These results suggest that in vitro metabolic studies using hepatocytes are more relevant with regard to stereoselectively predicting CLh of CAR than those using liver microsomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".