An enveloped virus-like particle vaccine expressing a stabilized prefusion form of the SARS-CoV-2 spike protein elicits potent immunity after a single dose
Bibliographic record
Abstract
Abstract Development of efficacious single dose vaccines would substantially aid efforts to stop the uncontrolled spread of the COVID-19 pandemic. We evaluated enveloped virus-like particles (eVLPs) expressing various forms of the SARS-CoV-2 spike protein and several adjuvants in an effort to identify a COVID-19 vaccine candidate efficacious after a single dose. The eVLPs expressing a modified prefusion form of SARS-CoV-2 spike protein were selected as they induced the highest antibody binding titers and neutralizing activity after a single injection in mice. Formulation of SARS-CoV-2 S eVLPs with aluminum phosphate resulted in balanced induction of IgG2 and IgG1 isotypes and antibody binding and neutralization titers were undiminished for more than 3 months after a single immunization. A single dose of this candidate, VBI-2902a (prefusion S eVLPs formulated with aluminum phosphate), protected Syrian golden hamsters from challenge with SARS-CoV-2 and supports the on-going clinical evaluation of VBI-2902a as a potential single dose vaccine against COVID-19. Highlights VBI-2902a is a VLP-based vaccine candidate against SARS-COV-2 VBI-2902a contains VLPs pseudotyped with a modified prefusion SARS-COV-2 S in Alum. VBI-2902a induces robust neutralization antibody response against SARS-COV-2 S VBI-2902a protects hamsters from SARS-CoV-2 induced lung inflammation A single dose of VBI-2902a provides protective benefit in hamsters
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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 | 0.000 |
| 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".