A Colon‐Targeted Adsorbent (DAV132) Does Not Affect the Pharmacokinetics of Warfarin or Clonazepam in Healthy Subjects
Bibliographic record
Abstract
Abstract DAV132 is a novel colon‐targeted adsorbent that prevents the deleterious impact of antibiotics on gut microbiota without modifying their systemic availability. A randomized, Latin‐square crossover, open‐label trial with 2 substudies in 18 and 24 healthy volunteers evaluated the pharmacokinetic (PK) bioequivalence of warfarin, a drug with a narrow therapeutic index (NTI), and clonazepam, both widely used for the treatment of chronic conditions, with or without coadministration of DAV132 7.5 g. PK parameters observed with single doses of 5 mg warfarin and 1 mg clonazepam when administered alone did not differ with the PK parameters when administered concomitantly with or 1 hour before DAV132. Geometric mean ratios (GMRs) for S‐warfarin, R‐warfarin, and clonazepam Cmax were 102.0, 102.8, and 91.9, respectively, after concomitant administration and 106.5, 107.5, and 95.0, respectively, when administered 1 hour before DAV132. After concomitant administration, GMRs for S‐warfarin, R‐warfarin, and clonazepam AUClast were 100.5, 100.2, and 94.9, respectively, and 101.9, 101.8, and 101.3, respectively, when administered 1 hour before DAV132. All GMR 90% confidence intervals fell within the prespecified 80% to 125% limit for bioequivalence, indicating a lack of drug‐drug interaction. In conclusion, DAV132 did not affect the systemic exposure of 2 NTI drugs absorbed in the proximal intestine.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".