Preclinical development of a replication-competent vesicular stomatitis virus-based Lassa virus vaccine candidate advanced into human clinical trials
Bibliographic record
Abstract
BACKGROUND: Lassa fever (LF) is a zoonotic haemorrhagic disease caused by Lassa virus (LASV), which is endemic in West African countries. The multimammate rat is the main animal reservoir and its geographic range is expected to expand due to influences like climate change and land usage, and this will place larger parts of Africa at risk. We conducted preclinical development on a promising experimental vaccine that allowed its advancement into human trials. METHODS: The LF vaccine is based on a vesicular stomatitis virus (VSV) vector in which the VSV glycoprotein (G) was replaced with the LASV glycoprotein complex (GPC). Earlier studies showed that this vaccine (VSVΔG-LASV-GPC) was efficacious in macaques, thus we regenerated VSVΔG-LASV-GPC using laboratory and documentation practices required to support vaccine manufacturing and human trials. The efficacy of the clinical vaccine candidate was assessed in cynomolgus macaques and more extensive immunologic analysis was performed than previously to investigate immune responses associated with protection. FINDINGS: A single VSVΔG-LASV-GPC vaccination elicited innate, humoural and cellular immune responses, prevented development of substantial LASV viraemia, and protected animals from disease. Vaccinated macaques developed polyfunctional antibodies and serum was shown to neutralize virus expressing GPCs representative of geographically diverse LASV lineages. INTERPRETATION: The VSVΔG-LASV-GPC clinical candidate elicited immunity that protected 10 of 10 vaccinated macaques from disease supporting its use in a clinical development program, which recently progressed to phase 2 clinical trials. Moreover, immunologic analysis showed that virus-neutralizing serum antibodies likely played a role in preventing LASV disease in vaccinated macaques. FUNDING: This work was supported by the Coalition for Epidemic Preparedness Innovations (CEPI), The National Institute of Allergy and Infectious Diseases (NIAID)/National Institutes of Health (NIH), The Bill and Melinda Gates Global Vaccine Accelerator Program, the Burroughs Wellcome Fund, and financial gifts and support by Nancy Zimmerman, Mark and Lisa Schwartz, and Terry and Susan Ragon.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".