Development and validation of broad-spectrum magnetic particle labelling processes for cell therapy manufacturing
Bibliographic record
Abstract
BACKGROUND: Stem cells are increasingly seen as a solution for many health challenges for an ageing population. However, their potential benefits in the clinic are currently curtailed by technical challenges such as high cell dose requirements and point of care delivery, which pose sourcing and logistics challenges. Cell manufacturing solutions are currently in development to address the supply issue, and ancillary technologies such as nanoparticle-based labelling are being developed to improve stem cell delivery and enable post-treatment follow-up. METHODS: The application of magnetic particle (MP) labelling to potentially scalable cell manufacturing processes was investigated in a range of therapeutically relevant cells, including mesenchymal stromal cells (MSC), cardiomyocytes (CMC) and neural progenitor cells (ReN). The efficiency and the biological effect of particle labelling were analysed using fluorescent imaging and cellular assays. RESULTS: Flow cytometry and fluorescent microscopy confirmed efficient labelling of monolayer cultures. Viability was shown to be retained post labelling for all three cell types. MSC and CMC demonstrated higher tolerance to MP doses up to 100× the standard concentration. This approach was also successful for MP labelling of suspension cultures, demonstrating efficient MP uptake within 3 h, while cell viability was unaffected by this suspension labelling process. Furthermore, a procedure to enable the storing of MP-labelled cell populations to facilitate cold chain transport to the site of clinical use was investigated. When MP-labelled cells were stored in hypothermic conditions using HypoThermosol solution for 24 h, cell viability and differentiation potential were retained post storage for ReN, MSC and beating CMC. CONCLUSIONS: Our results show that a generic MP labelling strategy was successfully developed for a range of clinically relevant cell populations, in both monolayer and suspension cultures. MP-labelled cell populations were able to undergo transient low-temperature storage whilst maintaining functional capacity in vitro. These results suggest that this MP labelling approach can be integrated into cell manufacturing and cold chain transport processes required for future cell therapy approaches.
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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 | 0.000 | 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".