Evaluation of the effect of food and gastric pH on the single‐dose pharmacokinetics of cabozantinib in healthy adult subjects
Bibliographic record
Abstract
Cabozantinib is a small molecule tyrosine kinase inhibitor that has been approved for the treatment of patients with progressive, metastatic medullary thyroid cancer. Cabozantinib exhibits a pH-dependent solubility profile in vitro. Two phase 1 clinical pharmacology studies were conducted in healthy subjects to evaluate whether factors that may affect cabozantinib solubility and gastric pH could alter cabozantinib bioavailability: a food effect study (study 1) and a drug-drug interaction (DDI) study with the proton pump inhibitor (PPI) esomeprazole (study 2). Following a high-fat meal (study 1), cabozantinib Cmax and AUC were increased (40.5% and 57%, respectively), and the median tmax was delayed by 2 hours. Cabozantinib should thus not be taken with food (patients should not eat for at least 2 hours before and at least 1 hour after administration). In the DDI study (study 2), the 90% confidence intervals (CIs) around the ratio of least-squares means of cabozantinib with esomeprazole versus cabozantinib alone for AUC0-inf were within the 80%-125% limits; the upper 90%CI for Cmax was 125.1%. Because of the low apparent risk of a DDI, concomitant use of PPIs or weaker gastric pH-altering agents with cabozantinib is not contraindicated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".