Efficacy and safety of AZR-MD-001 selenium sulfide ophthalmic ointment in adults with meibomian gland dysfunction over six months of treatment: A Phase 2, vehicle-controlled, randomized extension trial
Bibliographic record
Abstract
PURPOSE: To determine the efficacy and safety of AZR-MD-001 (0.5 % and 1.0 %) ophthalmic ointment, relative to vehicle, over 3-6 months of treatment, in participants with meibomian gland dysfunction (MGD). METHODS: This was a Phase 2, randomized, vehicle-controlled, multicenter extension clinical trial. Eligible participants were adults with MGD (meibomian gland secretion score (MGS) ≤12 out of 15 glands) who discontinued all other dry eye or MGD treatments. Participants were randomized 1:1:1 to apply AZR-MD-001 1.0 %, 0.5 %, or vehicle to the lower eyelids, twice weekly. Key exploratory endpoints included the least-squared mean difference between groups in the change from baseline in clinical signs (meibomian gland yielding score; MGYLS) and symptoms (Ocular Surface Disease Index; OSDI), at clinic visits at Month 4.5 and 6, and safety measures from 36 months. RESULTS: Participants (66.5 % female) were randomized, at baseline, to AZR-MD-001 0.5 % (n = 82), 1.0 % (n = 83), or vehicle (n = 80). Statistically significant improvements, compared to vehicle, were observed at Month 6 in MGYLS for both AZR-MD-001 groups (0.5 % group: 1.9, 95 % CI 0.9 to 2.8, P = 0.002; 1.0 % group: 1.1, 95 % CI 0.2 to 2.1, P = 0.026), and in OSDI score for the 0.5 % group (-4.5, 95 % CI -8.0 to -0.9, P = 0.0135). The most common adverse events for AZR-MD-001 were application site pain, superficial punctate keratitis and eye pain; most were mild to moderate in severity, and decreased in incidence over time. CONCLUSIONS: AZR-MD-001 (0.5 %) was efficacious in treating signs and symptoms of MGD over six months, with a lower observed incidence of new adverse events over time.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".