Clinical Immunogenicity of DaxibotulinumtoxinA for Injection in Glabellar Lines: Pooled Data from the SAKURA Phase 3 Trials
Bibliographic record
Abstract
DaxibotulinumtoxinA for Injection (DAXI) is a novel botulinum toxin type A product containing daxibotulinumtoxinA with a stabilizing excipient peptide (RTP004). DAXI immunogenicity was assessed in three phase 3 glabellar line studies (two placebo-controlled, single-dose studies and an open-label repeat-dose safety study). Binding antibodies to daxibotulinumtoxinA and RTP004 were detected by validated ELISAs. Samples positive for daxibotulinumtoxinA-binding antibodies were evaluated further for titer and neutralizing antibodies by mouse protection assay. Overall, 2786 subjects received DAXI and 2823 subjects were exposed to RTP004 as DAXI (n = 2786) or placebo (n = 37). Treatment-related anti-daxibotulinumtoxinA binding antibodies were detected in 21 of 2737 evaluable subjects (0.8%). No subject developed neutralizing antibodies. Treatment-related anti-RTP004 binding antibodies were detected in 35 (1.3%) of 2772 evaluable subjects. Binding antibodies were generally transient, of low titer (<1:200), and no subject had binding antibodies to both daxibotulinumtoxinA and RTP004. All subjects with treatment-induced binding antibodies to daxibotulinumtoxinA or RTP004 achieved none or mild glabellar line severity at Week 4 following each DAXI cycle, indicating no impact on DAXI efficacy. No subjects with binding antibodies to daxibotulinumtoxinA or RTP004 reported immune-related adverse events. This evaluation of anti-drug antibody formation with DAXI shows low rates of antibody formation to both daxibotulinumtoxinA and RTP004.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".