Recent Advancements in AAV-Vectored Immunoprophylaxis in the Nonhuman Primate Model
Bibliographic record
Abstract
Monoclonal antibodies (mAbs) are important treatment modalities for preventing and treating infectious diseases, especially for those lacking prophylactic vaccines or effective therapies. Recent advances in mAb gene cloning from naturally infected or immunized individuals has led to the development of highly potent human mAbs against a wide range of human and animal pathogens. While effective, the serum half-lives of mAbs are quite variable, with single administrations usually resulting in short-term protection, requiring repeated doses to maintain therapeutic concentrations for extended periods of time. Moreover, due to their limited time in circulation, mAb therapies are rarely given prophylactically; instead, they are generally administered therapeutically after the onset of symptoms, thus preventing mortality, but not morbidity. Adeno-associated virus (AAV) vectors have an established record of high-efficiency in vivo gene transfer in a variety of animal models and humans. When delivered to post-mitotic tissues such as skeletal muscle, brain, and heart, or to organs in which cells turn over slowly, such as the liver and lungs, AAV vector genomes assume the form of episomal concatemers that direct transgene expression, often for the lifetime of the cell. Based on these attributes, many research groups have explored AAV-vectored delivery of highly potent mAb genes as a strategy to enable long-term expression of therapeutic mAbs directly in vivo following intramuscular or intranasal administration. However, clinical trials in humans and studies in nonhuman primates (NHPs) indicate that while AAVs are a powerful and promising platform for vectored immunoprophylaxis (VIP), further optimization is needed to decrease anti-drug antibody (ADA) and anti-capsid antibody responses, ultimately leading to increased serum transgene expression levels and improved therapeutic efficacy. The following review will summarize the current landscape of AAV VIP in NHP models, with an emphasis on vector and transgene design as well as general delivery system optimization. In addition, major obstacles to AAV VIP, along with implications for clinical translation, will be discussed.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".