Use of eVLP-based vaccine candidates to broaden immunity against SARS-CoV-2 variants
Bibliographic record
Abstract
Abstract Rapid emergence of SARS-CoV-2 variants is a constant threat and a major hurdle to reach heard immunity. We produced VBI-2905a, an enveloped virus-like particle (eVLP)-based vaccine candidate expressing prefusion spike protein from the Beta variant that contains several escape mutations. VBI-2905a protected hamsters against infection with a Beta variant virus and induced high levels of neutralizing antibodies against Beta RBD. In a heterologous vaccination regimen, a single injection of VBI-2905a in animals previously immunized with VBI-2902, a vaccine candidate expressing S from ancestral SARS-CoV-2, hamsters were equally protected against Beta variant infection. As an alternate strategy to broaden immunity, we produced a trivalent vaccine expressing the prefusion spike protein from SARS-CoV-2 together with unmodifed S from SARS-CoV-1 and MERS-CoV. Relative to immunity induced against the ancestral strain, the trivalent vaccine VBI-2901a induced higher and more consistent antibody binding and neutralizing responses against a panel of variants including Beta, Delta, Kappa, and Lambda, with evidence for broadening of immunity rather than just boosting cross-reactive antibodies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".