Improving adeno‐associated vector yield in high density insect cell cultures
Bibliographic record
Abstract
BACKGROUND: Recombinant adeno-associated virus (rAAV) are the most promising vectors for gene therapy. However, large-scale rAAV production remains a challenge for the translation of rAAV-based therapeutic strategies to the clinic. The baculovirus expression vector system (BEVS) has been engineered to produce high rAAV titers in serum-free suspension cultures of insect cells. METHODS: The typical approach of rAAV production in BEVS has been based on a synchronous infection with three baculoviruses at high multiplicity of infection (MOI) [>3 plaque forming units (pfu)/cell]. An alternative approach is to co-infect at low MOI (0.1 pfu/cell). Both strategies (high and low MOI) were compared at a cell density of 1.0 x 10(6) cells/ml in shake-flask experiments. To increase the rAAV titer, a low MOI combined with an initial cell density at infection of 5.0 x 10(6) cells/ml, in fed-batch mode, was evaluated. Subsequently, the production strategy was validated in 3-l bioreactor runs. RESULTS: An increase of 210% in the rAAV titer (4.7 x 10(11) enhanced transduction units/l) was observed when using low MOI, an effect primarily caused by the increase in cell density. The fed-batch approach resulted in a seven-fold increase of rAAV yield. Controlled operations in bioreactor contributed to further increase the rAAV yield (2.8 x 10(14) vector genomes/l) by 25% in comparison to the shake flask results. CONCLUSIONS: This high yield production process using low MOIs and a feeding strategy successfully addresses several limitations of current rAAV production in insect cells and contributes to position the BEVS system as one of the most efficient for large-scale manufacturing of rAAV vectors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".