Preclinical Progress of Subunit and Live Attenuated Mycobacterium tuberculosis Vaccines: A Review following the First in Human Efficacy Trial
Bibliographic record
Abstract
Tuberculosis (TB) is the global leading cause of death from an infectious agent with approximately 10 million new cases of TB and 1.45 million deaths in 2018. Bacille Calmette-Guérin (BCG) remains the only approved vaccine for Mycobacterium tuberculosis (M. tb, causative agent of TB), however clinical studies have shown BCG has variable effectiveness ranging from 0–80% in adults. With 1.7 billion people latently infected, it is becoming clear that vaccine regimens aimed at both post-exposure and pre-exposure to M. tb will be crucial to end the TB epidemic. The two main strategies to improve or replace BCG are subunit and live attenuated vaccines. However, following the failure of the MVA85A phase IIb trial in 2013, more varied and innovative approaches are being developed. These include recombinant BCG strains, genetically attenuated M. tb and naturally attenuated mycobacteria strains, novel methods of immunogenic antigen discovery including for hypervirulent M. tb strains, improved antigen recognition and delivery strategies, and broader selection of viral vectors. This article reviews preclinical vaccine work in the last 5 years with focus on those tested against M. tb challenge in relevant animal models.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".