Efficacy and Safety of RelabotulinumtoxinA, a New Ready-to-Use Liquid Formulation Botulinum Toxin: Results From the READY-1 Double-Blind, Randomized, Placebo-Controlled Phase 3 Trial in Glabellar Lines
Bibliographic record
Abstract
BACKGROUND: RelabotulinumtoxinA (RelaBoNT-A, Galderma, Uppsala, Sweden) is an innovative, ready-to-use liquid botulinum toxin A, produced with PEARL (precipitation-free extraction and activity-preserving refined liquid) manufacturing technology, which yields a potent, complex-free formulation. OBJECTIVES: In the READY-1 study, efficacy and safety outcomes following a single RelaBoNT-A treatment for glabellar line correction were examined. METHODS: Adults with moderate to severe glabellar lines received RelaBoNT-A (50 U) or placebo in a 3:1 randomized, 6-month, phase 3, multicenter, double-blind study. Primary endpoints (examined at Month 1, maximum frown) comprised the composite ≥2-grade response, defined as ≥2-grades improvement from baseline on concurrent investigator (glabellar line investigator live assessment; GL-ILA) and participant (glabellar line subject live assessment; GL-SLA) severity scales (US endpoint), and the investigator-reported responder rate for participants scored as 0 (none) or 1 (mild) (GL-ILA scale only; EU endpoint). Participant satisfaction and treatment-emergent adverse events (TEAEs) were reported. RESULTS: Overall, 297 adults were randomized and treated. Month 1 composite ≥2-grade responder rate was 82.9% (RelaBoNT-A, n = 199) vs 0% (placebo, n = 67; P < .001). Month 1 investigator-reported none or mild responder rate was 96.3% (RelaBoNT-A) vs 4.5% (placebo; P < .001). GL-ILA scores remained higher with RelaBoNT-A (23.6% [none or mild]; 58.1% [≥1-grade improvement]) vs placebo (1.5%; 10.4%, respectively) through Month 6 (P < .001). In the Kaplan-Meier analysis, 75% still showed GL-ILA and GL-SLA improvements from baseline at 169 days (end of study). Participants reported onset of effect from Day 1 (39%) and satisfaction with natural-looking results (96.8%; Month 1). RelaBoNT-A-related TEAEs were low (3.6%) and typically mild. CONCLUSIONS: A single RelaBoNT-A treatment was effective and demonstrated a favorable safety profile. RelaBoNT-A provided significant improvements in glabellar line severity, high satisfaction, rapid onset, and enduring effectiveness throughout the 6-month study period.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".