A Cloned Recombinant Vesicular Stomatitis Virus-Vectored Marburg Vaccine, PHV01, Protects Guinea Pigs from Lethal Marburg Virus Disease
Bibliographic record
Abstract
Marburg virus (MARV) is a negative-sense, single-stranded RNA virus that belongs to the Filoviridae family. Despite having caused numerous outbreaks of severe hemorrhagic fever with high case fatality rates, there are still no clinically approved therapeutics or vaccines to treat or prevent MARV disease. Recombinant vesicular stomatitis viruses (rVSVs) expressing heterologous viral glycoproteins have shown remarkable promise as live-attenuated vaccine vectors, with an rVSV-based Ebola virus vaccine having received regulatory approval in the United States and numerous other countries. Analogous rVSV vaccine vectors have also been developed for MARV and have shown efficacy in several preclinical studies conducted in nonhuman primates. Here, we used a guinea pig model to confirm the protective efficacy of a cloned, rVSV-based candidate vaccine, termed PHV01, expressing the MARV variant Angola glycoprotein. Our results demonstrated that a single dose (2 × 106 PFU) of vaccine administered 28 days prior to challenge with a uniformly lethal dose of guinea-pig-adapted MARV variant Angola provided complete protection from death and disease. Moreover, protection was robust, with as little as 200 PFU of vaccine conferring significant protection. Not only does this study highlight the potential predictive value of the guinea pig model in the evaluation of MARV countermeasures, but it also demonstrates consistent and reproducible protection afforded by a clonal vaccine candidate. Indeed, this study identifies PHV01 as a suitable vaccine candidate for advanced development.
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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 | 0.001 | 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".