From Vial to Vein: Crucial Gaps in Mesenchymal Stromal Cell Clinical Trial Reporting
Bibliographic record
Abstract
Retrospective analysis of clinical trial outcomes is a vital exercise to facilitate efficient translation of cellular therapies. These analyses are particularly important for mesenchymal stem/stromal cell (MSC) products. The exquisite responsiveness of MSCs, which makes them attractive candidates for immunotherapies, is a double-edged sword; MSC clinical trials result in inconsistent outcomes that may correlate with underlying patient biology or procedural differences at trial sites. Here we review 45 North American MSC clinical trial results published between 2015 and 2021 to assess whether these reports provide sufficient information for retrospective analysis. Trial reports routinely specify the MSC tissue source, autologous or allogeneic origin and administration route. However, most methodological aspects related to cell preparation and handling immediately prior to administration are under-reported. Clinical trial reports inconsistently provide information about cryopreservation media composition, delivery vehicle, post-thaw time and storage until administration, duration of infusion, and pre-administration viability or potency assessments. In addition, there appears to be significant variability in how cell products are formulated, handled or assessed between trials. The apparent gaps in reporting, combined with high process variability, are not sufficient for retrospective analyses that could potentially identify optimal cell preparation and handling protocols that correlate with successful intra- and inter-trial outcomes. The substantial preclinical data demonstrating that cell handling affects MSC potency highlights the need for more comprehensive clinical trial reporting of MSC conditions from expansion through delivery to support development of globally standardized protocols to efficiently advance MSCs as commercial products.
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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 | 0.545 | 0.698 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier 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".