Fed‐batch bioreactor performance and cell line stability evaluation of the artificial chromosome expression technology expressing an IgG1 in chinese hamster ovary cells
Bibliographic record
Abstract
The artificial chromosome expression (ACE) technology system uses an engineered artificial chromosome containing multiple site-specific recombination acceptor sites for the rapid and efficient construction of stable cell lines. The construction of Chinese hamster ovary(CHO) cell lines expressing an IgG1 monoclonal antibody (MAb) using the ACE system has been previously described (Kennard et al., Biotechnol Bioeng. 2009;104:540-553). To further demonstrate the manufacturing feasibility of the ACE system, four CHO cell lines expressing the human IgG1 MAb 4A1 were evaluated in batch and fed-batch shake flasks and in a 2-L fed-batch bioreactor. The batch shake flasks achieved titers between 0.7 and 1.1 g/L, whereas the fed-batch shake flask process improved titers to 2.5–3.0 g/L. The lead 4A1 ACE cell line achieved titers of 4.0 g/L with an average specific productivity of 40 pg/(cell day) when cultured in a non optimized 2-L fed-batch bioreactor using a completely chemically defined process. Generational stability characterization of the lead 4A1-expressing cell line demonstrated that the cell line was stable for up to 75 days in culture. Product quality attributes of the 4A1 MAb produced by the ACE system during the stability evaluation period were unchanged and also comparable to existing expression technologies such as the CHO-dhfr system. The results of this evaluation demonstrate that a clonal, stable MAb-expressing CHO cell line can be produced using ACE technology that performs competitively using a chemically defined fed-batch bioreactor process with comparable product quality attributes to cell lines generated by existing technologies.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".