708. Process Development of Lentiviral Vectors for Large Scale Production Using a HEK293 Producer Cell Line
Bibliographic record
Abstract
Lentiviral vectors (LVs) are promising vectors for gene therapy. Most often, they are used to deliver a functional copy of a gene to sustainably replace a defective or missing gene. However, processes for LVs must be improved to increase the yield, facilitate the scale up and satisfy Health regulatory agencies. For these reasons, we have developed and optimized a LVs production process in serum-free medium using an inducible HEK293 producer cell line which possesses the capacity to grow in suspension culture. By adding two inducing molecules, (cumate and doxycycline) this cell line produces LVs pseudotyped with the protein G of the vesicular stomatitis virus without the need of any transfection. Our tested LV carried an expression cassette for GFP to facilitate LV quantification. To optimize the process, a design of experiment (DoE) was prepared which included the study of different culture media, high cell density production using six cell boosts commercially available and the addition of sodium butyrate, caffeine and valproic acid. We found that two cell boosts were outperforming the other cell boosts tested. At the present time, two commercial media (Hycell TransFx-H and SFM4TransFx-293 media) were our best candidates to maximize viral titer by achieving high cell density culture. In parallel, a LV carrying the cDNA for a shorter version of dystrophin (mini-dystrophin) was constructed. The truncated version of the dystrophin was produced by transient transfection in 293A cells and its presence was confirmed by western blot. We are planning to evaluate if the optimal conditions for the production of LV-GFP will be also applicable to LV-mini-dystrophin, a LV encoding a much longer transgene than GFP (0.7 kb vs 5.8 kb). This LV could be first evaluated for cell therapy in animal models and later, in patients suffering from Duchenne muscular dystrophy, where the dystrophin gene is defective and the protein is absent.
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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 | 0.000 |
| 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".