713. Optimization and Scale-Up of a Manufacturing Process for Clinical-Grade Adenovirus-Based Vectors
Bibliographic record
Abstract
We have developed a manufacturing protocol for clinical-grade Adenovirus-based vectors utilizing suspension 293 cells grown with chemically defined media in disposable spinner flasks. We have manufactured four batches of clinical-grade Adenovirus vectors utilizing this protocol, and some vectors have been administered in TB or cancer vaccine clinical trials in Canada. The maximum volume for a batch was from a 30-liter infected cell culture consisting of three lots with 10 liters. Each 10-liter lot was purified by cesium chloride density gradient ultracentrifugation and desalted by a Biogel column. The purified vectors were then pooled, filtered and filled into cryovials. In an effort to increase manufacturing capacity, we have investigated the use of a Pall XRS-20 Bioreactor with a maximum cell culture capacity of 20 liters. We assessed cell growth kinetics/infection kinetics and found that at the minimum, we can achieve triple the maximum cell density compared with the use of spinner flasks. We have observed virus yields similar to what can be achieved with spinner flasks, and are currently optimizing the infection protocol to assess if virus yields can still be improved. In order to address the scale-up concerns associated with the cesium chloride density gradient ultracentrifugation method, we are also developing a chromatography-based virus purification protocol. We are using a high-throughput test protocol to identify the critical process parameters (e.g. specific buffer species, pH, ionic strength) in resin binding experiments that achieve the required removal of impurities but also maintain immunogenic activity. A design-of-experiment strategy is being used to minimize the overall number of experiments.
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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 | 0.000 | 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".