ReviewStem cells (Dayton, Ohio)2026
Opportunities with artificial intelligence in assessing the potency of mesenchymal stromal cells.
Review in Stem cells (Dayton, Ohio), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- The role and mechanisms of mesenchymal stem cells in postoperative cognitive dysfunction via immune network regulation.Stem cell research & therapy · 2026Review
- Cell-based therapies of autoimmune diseases in the context of artificial intelligence development.Clinical and experimental medicine · 2026Review
- Rational design of immunological programs for functional regenerative niches.Materials today. Bio · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Determining the potency of MSCs is a critical component of their application as cellular therapies. The function of MSCs does not rely on a single mechanism but rather on overlapping and cumulative effector pathways, which necessitates the assay matrix strategy in potency analysis. Artificial intelligence (AI) tools can significantly enhance the assay matrix strategy by generating novel potency scores that capture unified critical quality attributes that may not be readily discernible through human analysis. AI can provide precise potency metrics for investigational MSC products by comparing them to appropriate controls. The next generation of MSC potency analysis will increasingly rely on AI tools, as they can match patients with MSC products exhibiting the most appropriate potency profiles for personalized and targeted therapies. A significant challenge in deploying AI tools is the need for robust predictors of efficacy that relates to the potency of investigational MSC products. Nevertheless, AI has the potential to stratify patients who are most likely to respond to MSC therapy by leveraging clinical data in combination with detailed potency analyses. We discuss these opportunities and challenges in this perspective article.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.