Lack of pharmacokinetic interaction between retigabine and phenobarbitone at steady‐state in healthy subjects
Bibliographic record
Abstract
AIMS: To evaluate potential pharmacokinetic interactions between phenobarbitone and retigabine, a new antiepileptic drug. METHODS: Fifteen healthy men received 200 mg of retigabine on day 1. On days 4-32, phenobarbitone 90 mg was administered at 22.00 h. On days 26-32, increasing doses of retigabine were given to achieve a final dose of 200 mg every 8 h on day 32. The pharmacokinetics of retigabine were determined on days 1 and 32, and those for phenobarbitone on days 25 and 31. RESULTS: After administration of a single 200 mg dose, retigabine was rapidly absorbed and eliminated with a mean terminal half-life of 6.7 h, a mean AUC of 3936 ng x ml(-1) x h and a mean apparent clearance of 0.76 l x h(-1) x kg(-1). Similar exposure to the partially active acetylated metabolite (AWD21-360) of retigabine was observed. After administration of phenobarbitone dosed to steady-state, the pharmacokinetics of retigabine at steady-state were similar (AUC of 4433 ng x ml(-1) x h and t1/2 of 8.5 h) to those of retigabine alone. The AUC of phenobarbitone was 298 mg x l(-1) x h when administered alone and 311 mg x ml(-1) x h after retigabine administration. The geometric mean ratios and 90% confidence intervals of the AUC were 1.11 (0.97, 1.28) for retigabine, 1.01 (0.88, 1.06) for AWD21-360 and 1.04 (0.96, 1.11) for phenobarbitone. Individual and combined treatments were generally well tolerated. One subject was withdrawn from the study on day 10 due to severe abdominal pain. Headache was the most commonly reported adverse event. No clinically relevant changes were observed in the electrocardiograms, vital signs or laboratory measurements. CONCLUSIONS: There was no pharmacokinetic interaction between retigabine and phenobarbitone in healthy subjects. No dosage adjustment is likely to be necessary when retigabine and phenobarbitone are coadministered to patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".