ArticleCell discovery2023
A live-cell image-based machine learning strategy for reducing variability in PSC differentiation systems.
Article in Cell discovery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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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.
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Who cites it
27 citing papers in PubMed, 40 citations in OpenAlex.
- Engineering human multi-organ tissue chip niches for drug absorption, distribution, metabolism, excretion and toxicity prediction.Nature biomedical engineering · 2026Review
- A Generative AI Framework to Predict Cardiomyocyte Contraction Function from Single Static Images.Advanced intelligent discovery · 2026Article
- Signaling mechanisms and dynamics governing the myocardial-epicardial fate switch during human cardiogenesis.Science advances · 2026Article
- Machine Learning Models of Phase Contrast Images Predict Efficiency of Human Pluripotent Stem Cell Differentiation to Cardiomyocytes.Biotechnology and bioengineering · 2026Article
- Clinical translational research on stem cell products: prospects and challenges.Signal transduction and targeted therapy · 2026Review
- A Generative AI Framework to Predict Cardiomyocyte Contraction Function from Single Static Images.bioRxiv : the preprint server for biology · 2026Article
- Cell-MICS: Detecting Immune Cells With Label-Free Two-Photon Autofluorescence and Deep Learning.Journal of biophotonics · 2026Article
- Single-Cell Multi-Omics Reveal Gene Regulatory Mechanisms Underlying Cardiac Embryonic Development.Genes · 2026Review
- Integrating living biomaterials into neuroelectronic systems.Biomedical engineering letters · 2026Review
- Artificial intelligence-driven nano-enhanced stem cell therapy for neurodegenerative diseases: from rational design to clinical translation.Journal of nanobiotechnology · 2026Review
- Beyond Transplantation: Engineering Neural Cell Therapies and Combination Strategies for Spinal Cord Repair.Brain sciences · 2026Review
- Early multi-omic signatures and machine learning models predict cardiomyocyte differentiation efficiency and enable robust hPSC differentiation to cardiomyocytes.bioRxiv : the preprint server for biology · 2026Article
- Leveraging AI for cell biology discovery.Biochemical Society transactions · 2026Review
- Machine Learning in Stem Cell Research: From Biological Data to Clinical Translation.Computational and structural biotechnology journal · 2026Review
- Smarter stem cells: how AI is supercharging iPSC technology.Cell and tissue research · 2025Review
- Stem Cell Therapy in Ischemic Heart Failure.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2025Review
- Single-cell multi-omics and machine learning for dissecting stemness in cancer.Briefings in bioinformatics · 2025Review
- Engineering a controlled cardiac multilineage co-differentiation process using statistical design of experiments.Stem cell research & therapy · 2025Article
- Enhancing human pluripotent stem cell differentiation to cardiomyocytes through cardiac progenitor reseeding and cryopreservation.iScience · 2025Article
- AI-driven 3D bioprinting for regenerative medicine: From bench to bedside.Bioactive materials · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
24 authors at 3 institutions in 2 countries.
Funding
Abstract
The differentiation of pluripotent stem cells (PSCs) into diverse functional cell types provides a promising solution to support drug discovery, disease modeling, and regenerative medicine. However, functional cell differentiation is currently limited by the substantial line-to-line and batch-to-batch variabilities, which severely impede the progress of scientific research and the manufacturing of cell products. For instance, PSC-to-cardiomyocyte (CM) differentiation is vulnerable to inappropriate doses of CHIR99021 (CHIR) that are applied in the initial stage of mesoderm differentiation. Here, by harnessing live-cell bright-field imaging and machine learning (ML), we realize real-time cell recognition in the entire differentiation process, e.g., CMs, cardiac progenitor cells (CPCs), PSC clones, and even misdifferentiated cells. This enables non-invasive prediction of differentiation efficiency, purification of ML-recognized CMs and CPCs for reducing cell contamination, early assessment of the CHIR dose for correcting the misdifferentiation trajectory, and evaluation of initial PSC colonies for controlling the start point of differentiation, all of which provide a more invulnerable differentiation method with resistance to variability. Moreover, with the established ML models as a readout for the chemical screen, we identify a CDK8 inhibitor that can further improve the cell resistance to the overdose of CHIR. Together, this study indicates that artificial intelligence is able to guide and iteratively optimize PSC differentiation to achieve consistently high efficiency across cell lines and batches, providing a better understanding and rational modulation of the differentiation process for functional cell manufacturing in biomedical applications.
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.