The Pharmacodynamics, Pharmacokinetics, and Safety of Arhalofenate in Combination with Febuxostat When Treating Hyperuricemia Associated with Gout
Bibliographic record
Abstract
Objective. Arhalofenate (ARH), in development for gout, has uricosuric and anti-flare activities. ARH plus febuxostat (FBX) were evaluated in subjects with gout for serum uric acid (SUA) lowering, drug interaction, and safety. Methods. Open phase II trial in gout volunteers ( NCT02252835 ). Cohort 1 received ARH 600 mg for 2 weeks, followed by sequential 1-week co-administration of FBX 80 mg followed by 40 mg. FBX 40 mg was continued alone for 2 weeks. Cohort 2 received ARH 800 mg for 2 weeks, followed by sequential 1-week co-administration of FBX 40 mg followed by 80 mg. FBX 80 mg was continued alone for 2 weeks. SUA, its fractional excretion (FEUA), and plasma oxypurines were assessed. Pharmacokinetics of FBX and ARH were determined alone and in combination for cohort 2. Results. Baseline mean SUA was 9.4 mg/dl for cohort 1 (n = 16) and 9.2 mg/dl for cohort 2 (n = 16). The largest SUA decrease (63%) was observed with ARH 800 mg + FBX 80 mg, with all subjects reaching SUA < 6 mg/dl and 93% < 5 mg/dl. The area under the curve (AUC)(0-t)of ARH acid + FBX/ARH acid was 108%. The AUC(0-t)of FBX + ARH acid/FBX was 87%. As expected, FBX increased oxypurines and increases were unaffected by ARH co-administration. Baseline FEUA were low (3.5%–4.6%) and ARH increased them toward normal without overexcretion of UA. ARH was well tolerated and appeared safe. Conclusion. ARH and FBX lowered SUA by complementary mechanisms. The combination provided greater decreases than each drug alone. The combination was well tolerated and appeared safe. Trial registration: NCT02252835 .
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".