Past, Present, and Future of Viral Vector Vaccine Platforms: A Comprehensive Review
Bibliographic record
Abstract
Over the past several decades, viral vector-based vaccines have emerged as some of the most versatile and potent platforms in modern vaccinology. Their capacity to deliver genetic material encoding target antigens directly into host cells enables strong cellular and humoral immune responses, often superior to what traditional inactivated or subunit vaccines can achieve. This has accelerated their application to a wide array of pathogens and disease targets, from well-established threats like HIV and malaria to emerging infections such as Ebola, Zika, and SARS-CoV-2. The COVID-19 pandemic further highlighted the agility of viral vector platforms, with several adenovirus-based vaccines quickly authorized and deployed on a global scale. Despite these advances, significant challenges remain. One major hurdle is pre-existing immunity against commonly used vector backbones, which can blunt vaccine immunogenicity. Rare but serious adverse events, including vector-associated inflammatory responses and conditions like vaccine-induced immune thrombotic thrombocytopenia (VITT), have raised important safety considerations. Additionally, scaling up manufacturing, ensuring consistency in large-scale production, meeting rigorous regulatory standards, and maintaining equitable global access to these vaccines present profound logistical and ethical dilemmas. In response to these challenges, the field is evolving rapidly. Sophisticated engineering strategies, such as integrase-defective lentiviral vectors, insect-specific flaviviruses, chimeric capsids to evade neutralizing antibodies, and plug-and-play self-amplifying RNA approaches, seek to bolster safety, enhance immunogenicity, circumvent pre-existing immunity, and streamline production. Lessons learned from the COVID-19 pandemic and prior outbreaks are guiding the development of platform-based approaches designed for rapid deployment during future public health emergencies. This review provides an exhaustive, in-depth examination of the historical evolution, immunobiological principles, current platforms, manufacturing complexities, regulatory frameworks, known safety issues, and future directions for viral vector-based vaccines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".