Bibliographic record
Abstract
HEK-293 cell lines have been widely used for over 35 years by the scientific community. Currently HEK-293 cells are the most efficient system for the improved production of ribosomal proteins and viral vectors by large-scale transfection of suspension-growing cells in serum-free medium. Also, it is the most established cell line for the production of adeno- and adeno-associated viruses, retro- and lentiviruses for gene therapy applications. Additionally HEK-293 cells sustain replication of many viruses that are evaluated as vaccines or viro-therapeutic agents. Consequently numerous viral vectors produced in HEK-293 cells have been approved for phase II and phase III clinical trials. In this presentation, major achievements in process developments completed at NRC to support the large scale manufacturing of viral vectors and vaccines using HEK-293 technology platform will be reviewed. In particular, we will discuss the development of REOLYSIN®, an oncolytic reovirus type 3 Dearing based therapeutic that is currently evaluated in phase III. The REOLYSIN® manufacturing process was scaled-up to a 100 L operation volume to support multicenter clinical evaluation. Advanced online monitoring tools allowed a very precise characterisation of viral infection and production kinetics to demonstrate process robustness, define critical process parameters and establish the process operating space according to the Quality-by-Design guidelines. Through different examples, the presentation will also discuss practises and experiences at NRC in supporting translational research and technology transfer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".