Assessment of Competitive and Mechanism-Based Inhibition by Clarithromycin: Use of Domperidone as a CYP3A Probe-Drug Substrate and Various Enzymatic Sources Including a New Cell-Based Assay with Freshly Isolated Human Hepatocytes
Bibliographic record
Abstract
Clarithromycin is involved in a large number of clinically relevant drug-drug interactions. Discrepancies are observed between the magnitude of drug interactions predicted from in vitro competitive inhibition studies and changes observed clinically in the plasma levels of affected CYP3A substrates. The formation of metabolic-intermediate complexes has been proposed to explain these differences. The objectives of our study were: 1) to determine the competitive inhibition potency of clarithromycin on the metabolism of domperidone as a CYP3A probe drug using human recombinant CYP3A4 and CYP3A5 isoenzymes, human liver microsomes and cultured human hepatocytes; 2) to establish the modulatory role of cytochrome b5 on the competitive inhibition potency of clarithromycin; 3) to demonstrate the clarithromycin-induced formation of CYP450 metabolic-intermediate complexes in human liver microsomes; and 4) to determine the extent of CYP3A inhibition due to metabolic-intermediate complex formation using human liver microsomes and cultured human hepatocytes. At high concentrations (100 µM), clarithromycin had weak competitive inhibition potency towards CYP3A4 and CYP3A5. Inhibition potency was further decreased by the addition of cytochrome b5 (9-19%). Clarithromycin-induced metabolic-intermediate complexes were revealed by spectrophotometry analysis using human liver microsomes while time- and concentration-dependent mechanism-based inhibitions were quantified using isolated hepatocytes. These results indicate that mechanism-based but not competitive inhibition of CYP3As is the major underlying mechanism of drug-drug interactions observed clinically with clarithromycin. Drug interactions between clarithromycin and several CYP3A substrates are predicted to be insidious; the risk of severe adverse events should increase over time and persist for a few days after cessation of the drug.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".