Super7 passaging method to improve Chinese hamster ovary cell fed‐batch performance
Bibliographic record
Abstract
Chinese hamster ovary (CHO) cells are widely used to manufacture biopharmaceuticals, most of all monoclonal antibodies (mAbs). Some CHO cell lines exhibit production instability, where the productivity of the cells decreases as a function of time in culture. To counter this, we designed a passaging strategy that, rather than maximizing the time spent in log-growth phase, mimics the first 7 days of a fed-batch production process. Cultures passaged using this method had lower net growth rates and were more oxidative throughout 6 weeks of passaging. Fed-batch cultures inoculated by cells passaged using this method had increased net growth rates, oxidative metabolism, and volumetric productivity compared to cells passaged using a conventional strategy. Cells from unstable cell lines passaged by this new method produced 80%-160% more mAbs per unit volume than cells passaged by a conventional method. This new method, named Super7, provides the ability to mitigate the impact of production instability in CHO-K1 cell lines without a need for further cell line creation, genetic engineering, or medium development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".