Process development for high-titer production of adenovirus devoid of replication-competent particles in suspension-adapted complementing A549 cell culture
Bibliographic record
Abstract
Abstract Adenovirus is one of the most attractive viral vectors for therapeutic vaccines and gene therapy with the caveat that replication-competent adenoviruses (RCA) can be produced. To remediate this problem, engineered A-549 adenoviral vector complementing cells (SF-BMAdR cells) were previously generated by our organization for the production of E1-deleted adenoviral vectors without RCA. However, the production process remained to be improved for high titer production and scalability, as cost-effective and scalable biomanufacturing processes are critical for commercializing adenovirus-based vaccines and gene therapy. In this study, we first explored the potential of batch and fed-batch culture to increase maximum cell density and virus productivity by evaluating four different commercially available serum-free media and their combinations, and several feeds. A mixture (1:1) of two culture media improved the maximum cell density from 2.8 × 10 6 cells/mL obtained in the current batch culture to 4.2 × 10 6 cells/mL, and increased the virus productivity by 70% at a titer of 1.5 × 10 10 vp/mL. The fed-batch culture process, however, did not yield a significant improvement in either the maximum cell density or virus productivity. In contrast, batch culture with one medium replacement not only increased the cell growth but also resulted in an additional 70% improvement in the virus productivity at 2.6 × 10 10 vp/mL. The virus productivity was further increased to 6.3 × 10 10 vp/mL in a 3 L bioreactor perfusion culture infected at 7.0 × 10 6 cells/mL. This titer is 7.5 folds of the titer obtained in the current process. This study demonstrated the potential for a drastic improvement in the productivity of RCA-free adenovirus in the SF-BMAdR culture process. Furthermore, various processes developed fulfill different operational needs in manufacturing of RCA-free adenovirus to meet the increasing demands for therapeutic vaccines and gene therapy.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".