479. An Optimized DNA Vaccine Formulation Protects Against Lethal Ebola Makona Virus Challenge in Non-Human Primates and Elicits Robust Immune Responses
Bibliographic record
Abstract
The West African Ebola hemorrhagic fever virus outbreak is the most wide-spread occurrence of the virus to-date. Over 28 000 cases have been confirmed, however the actual figures are likely much higher. There are currently no approved vaccines but several clinical trials of viral vector candidates are underway and evidence suggests that the VSV-ZEBOVGP vaccine can prevent further transmission of the virus. However, the considerable drawback of anti-vector immunity still remains to be addressed and reports from human clinical trials observe the presence of adverse events including fever, blistering, and development of arthritis/joint pain which may limit some applications of this vaccine. Therefore, investigating alternative immunization approaches is important. We designed a DNA vaccine formulation expressing 3 synthetic Zaire Ebola virus (EBOV) glycoproteins (GP): 2 designed based on GP sequence alignments (1976-2014) and a 3rd construct matched to a 2014 outbreak strain. Plasmid IL-12 (pIL-12) was also included as an adjuvant to further enhance cellular immune responses. We administered this multivalent GP DNA vaccine formulation in macaques following a DNA-DNA prime-boost immunization regimen. Macaques (n=3 or 4/group) received the multivalent GP DNA formulation + pIL-12 by intramuscular delivery followed by electroporation. We assayed differences in immunogenicity and monitored protection between different doses, regimens (2, 3, 4, and 5 injections), and different spacing intervals between subsequent doses. Both antibody and T cell responses were observed in 83% of animals 2 weeks following the first injection and 100% of animals after the 2nd injection. The macaques were challenged with a lethal dose of the EBOV Guinea-Makona outbreak strain (1000pfu, 7-U virus) and monitored for 28 days following infection. 100% of animals receiving at least 3 injections at 4 week intervals survived lethal challenge. Animals were fully protected against signs of disease and did not exhibit elevated blood chemistry. Interestingly, 50% of animals receiving 2 injections survived lethal challenge. The surviving animals exhibited minimal signs of disease, suggesting that with further optimization complete protection with 2 injections is potentially achievable. In additional optimization studies in mice, single injections were found to be 100% protective and we observed that long-term immune responses 8 months post vaccination were induced. Further studies in NHP are now in progress.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".