Scalable production of adeno‐associated virus type 2 vectors via suspension transfection
Bibliographic record
Abstract
Vectors derived from adeno-associated virus type 2 (AAV2) are promising gene delivery vehicles, but it is still challenging to get the large number of recombinant adeno-associated virus (rAAV) particles required for large animal and clinical studies. Current transfection technology requires adherent cultures of HEK 293 cells that can only be expanded by preparing multiple culture plates. A single large-scale suspension culture could replace these multiple culture preparations, but there is currently no effective co-transfection scheme for generating rAAV from cells in suspension culture. Here, we weaned HEK 293 cells to suspension culture using hydrogel-coated six-well culture plates and established an efficient transfection strategy suitable for these cells. Then the cultures were gradually scaled up. We used linear polyethylenimine (PEI) to mediate transfection and obtained high transfection efficiencies ranging from 54% to 99%, thereby allowing efficient generation of rAAV vectors. Up to 10(13) rAAV particles and, more importantly, up to 10(11) infectious particles were generated from a 2-L bioreactor culture. The suspension-transfection strategy of this study facilitates the homogeneous preparation of rAAV at a large scale, and holds further potential as the basis for establishing a manufacturing process in a larger bioreactor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".