Advancements in molecular design and bioprocessing of recombinant adeno‐associated virus gene delivery vectors using the insect‐cell baculovirus expression platform
Bibliographic record
Abstract
Despite rapid progress in the field, scalable high-yield production of adeno-associated virus (AAV) is still one of the critical bottlenecks the manufacturing sector is facing. The insect cell-baculovirus expression vector system (IC-BEVS) has emerged as a mainstream platform for the scalable production of recombinant proteins with clinically approved products for human use. In this review, we provide a detailed overview of the advancements in IC-BEVS for rAAV production. Since the first report of baculovirus-induced production of rAAV vector in insect cells in 2002, this platform has undergone significant improvements, including enhanced stability of Bac-vector expression and a reduced number of baculovirus-coinfections. The latter streamlining strategy led to the eventual development of the Two-Bac, One-Bac, and Mono-Bac systems. The one baculovirus system consisting of an inducible packaging insect cell line was further improved to enhance the AAV vector quality and potency. In parallel, the implementation of advanced manufacturing approaches and control of critical processing parameters have demonstrated promising results with process validation in large-scale bioreactor runs. Moreover, optimization of the molecular design of vectors to enable higher cell-specific yields of functional AAV particles combined with bioprocess intensification strategies may also contribute to addressing current and future manufacturing challenges.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".