Lack of a pharmacokinetic interaction between lansoprazole or pantoprazole and theophylline
Bibliographic record
Abstract
AIM: To study the potential pharmacokinetic interaction between lansoprazole or pantoprazole and theophylline at steady state. METHODS: Theophylline 200 mg extended-release formulation was administered twice daily on days 1-11 to 30 healthy, non-smoking males. On days 5-11, 15 subjects received concomitant lansoprazole 30 mg once daily (o.d.) and 15 subjects received concomitant pantoprazole 40 mg o.d. RESULTS: No significant changes in the steady-state theophylline maximum plasma concentration (Cmax), time to Cmax (Tmax), minimum plasma concentration (Cmin), area under the plasma concentration-time curve over the 12-h dosing interval (AUC0-12), or apparent total oral clearance (CL/F) were observed within the two treatment groups when theophylline was administered alone or in combination with lansoprazole or pantoprazole. In addition, no significant differences in the changes of steady-state theophylline pharmacokinetics from day 4 to day 11 were noted between the two treatment groups. Treatment with theophylline in combination with either lansoprazole or pantoprazole was well tolerated. All adverse events were transient and rated mild to moderate in severity. CONCLUSION: Co-administration of either lansoprazole or pantoprazole in healthy subjects does not significantly affect the steady-state pharmacokinetics of theophylline at the therapeutic doses tested.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".