Recent Advances in Therapeutics and Manufacturing Processes of Recombinant Adeno-Associated Virus for the Treatment of Lung Diseases
Bibliographic record
Abstract
Developing delivery vectors capable of transducing genetic material across the lung epithelia and mucus barrier is a major challenge and of great interest to enable gene therapies to treat pulmonary diseases. Recombinant Adeno-associated Viruses (rAAVs) have emerged as attractive candidates among viral and non-viral vectors due to their broad tissue tropism, ability to transduce dividing and quiescent cells, and their safety profile in current human applications. While rAAVs have demonstrated safety in earlier clinical trials for lung disease applications, there are still some limitations regarding rAAV-transgene delivery in pulmonary cells. Thus, further improvements in rAAV engineering are needed to enhance the effectiveness of rAAV-based therapies for lung diseases. Such therapies could benefit patients with chronic lung diseases, such as asthma, chronic obstructive pulmonary disease, pulmonary hypertension, and cystic fibrosis, among others, by regulating hereditary gene mutations or acquired gene deregulations causing these conditions. Alongside therapeutic development, advances in the rAAV production process are essential to meet increasing production demands, while reducing manufacturing costs. This review discusses current challenges and recent advances in the field of rAAV engineering and manufacturing to encourage the clinical development of new pulmonary gene therapy treatments.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".