International Society for Cellular Therapy perspective on immune functional assays for mesenchymal stromal cells as potency release criterion for advanced phase clinical trials
Bibliographic record
Abstract
Mesenchymal stromal cells (MSCs) as a pharmaceutical for ailments characterized by pathogenic autoimmune, alloimmune and inflammatory processes now cover the spectrum of early- to late-phase clinical trials in both industry and academic sponsored studies. There is a broad consensus that despite different tissue sourcing and varied culture expansion protocols, human MSC-like cell products likely share fundamental mechanisms of action mediating their anti-inflammatory and tissue repair functionalities. Identification of functional markers of potency and reduction to practice of standardized, easily deployable methods of measurements of such would benefit the field. This would satisfy both mechanistic research as well as development of release potency assays to meet Regulatory Authority requirements for conduct of advanced clinical studies and their eventual registration. In response to this unmet need, the International Society for Cellular Therapy (ISCT) addressed the issue at an international workshop in May 2015 as part of the 21st ISCT annual meeting in Las Vegas. The scope of the workshop was focused on discussing potency assays germane to immunomodulation by MSC-like products in clinical indications targeting immune disorders. We here provide consensus perspective arising from this forum. We propose that focused analysis of selected MSC markers robustly deployed by in vitro licensing and metricized with a matrix of assays should be responsive to requirements from Regulatory Authorities. Workshop participants identified three preferred analytic methods that could inform a matrix assay approach: quantitative RNA analysis of selected gene products; flow cytometry analysis of functionally relevant surface markers and protein-based assay of secretome. We also advocate that potency assays acceptable to the Regulatory Authorities be rendered publicly accessible in an "open-access" manner, such as through publication or database collection.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
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".