A phase 3 randomized safety and immunogenicity trial of mRNA-1010 seasonal influenza vaccine in adults
Bibliographic record
Abstract
Messenger RNA (mRNA)-based influenza vaccines have the potential to improve upon limitations of current vaccine approaches to seasonal influenza. Here we report findings on the primary and secondary objectives of the safety, reactogenicity, and humoral immunogenicity of the quadrivalent mRNA vaccine, mRNA-1010, versus licensed standard-dose and high-dose quadrivalent influenza vaccines from a three-part, phase 3 clinical trial in adults aged ≥18 years (Part A), 18–64 years (Part B), and ≥ 65 years (Part C) ( NCT05827978 ). A single 50-μg dose of mRNA-1010 elicited hemagglutination inhibition titers against vaccine-matched strains that were statistically noninferior and superior to licensed standard-dose and high-dose egg-based quadrivalent vaccine comparators. Solicited adverse reactions were more frequent with receipt of mRNA-1010; adverse reactions were lower in frequency and severity among adults aged ≥65 years than younger adults. No safety concerns were identified. These findings support the potential benefit of mRNA-1010 as a seasonal influenza vaccine. • Seasonal influenza viral infections are a global health concern. • mRNA platform may improve upon limitations of current influenza vaccine technology. • mRNA-1010 is an mRNA-based vaccine targeting seasonal influenza A and B strains. • mRNA-1010 elicited strong immune responses in adults of all ages. • No safety concerns were identified with mRNA-1010 in this phase 3 study.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".