Abstract A036: Development of a stirred-tank bioreactor scale-up approach to allogeneic natural killer cell culture
Bibliographic record
Abstract
Abstract Natural killer (NK) cells are innate lymphocytes that play a critical role in the immune response, as they recognize and eliminate virus-infected, cancerous, and other abnormal cells in an antigen-independent manner. This unique method of recognition makes NK cells an attractive target for utilization as an immunotherapy, as studies have demonstrated they reduce both the induction of graft-versus-host disease and the risk of cytokine release syndrome compared to T-cell based therapies. Additionally, these advantages over canonical T-cell therapies make NK therapies attractive candidates for allogeneic, as opposed to autologous, products. Given their cost-effective scale-up potential, developing a stirred-tank bioreactor (STR)-based NK cell expansion platform to achieve clinical-level expansion is of significant interest, as it would reduce the cost of producing such therapies and improve patient accessibility. To test ideal culture conditions for STR expansion, NK cells were first isolated from healthy donor Leukopaks prior to cryopreservation. Frozen, isolated NK cells were then thawed, co-cultured with varying ratios of irradiated K562 cells and supplemental cytokines from Cytiva in a 6-well G-Rex or DASbox® STR. Finally, cells were harvested for downstream analytics, including identity and functional characterization by flow cytometry and potency assays. A fold expansion of greater than 100 was achieved once the ratio of irradiated K562 to NK cells was optimized. One of the primary challenges encountered was donor-to-donor variation, not only with respect to proliferative capacity, but NK functional phenotype and activity as well. Therefore, a small-scale donor screen was conducted and donors with similar proliferative and functional capabilities were selected for large-scale expansion. Future work will focus on optimizing NK cell transduction to enable genetic customization and scaling-up to a clinically-relevant STR. The successful small-scale NK expansion in an STR demonstrated here lays the groundwork for an expansion platform that enables the manufacturing of various NK-based therapeutics at clinical scale. Citation Format: Mathura Yogalingam, Rebecca Jagroop, Alireza Khalajzadeh, Thergiory Irrazabal, Melissa Perea, Pooja Pushparaj, Roxana Roshankhah, Paul Bowles, Michael Le. Development of a stirred-tank bioreactor scale-up approach to allogeneic natural killer cell culture [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A036.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".