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Record W4414064643 · doi:10.1101/2025.09.07.674777

Growth Factor-Based Manufacturing of Human Pluripotent Stem Cell-Derived Cardiomyocytes Using the Vertical Wheel Bioreactor System

2025· preprint· en· W4414064643 on OpenAlexafffund
Faisal J. Alibhai, Tamilla Valdman Sadikov, Carl Montague, Lorena V. Cortés-Medina, Ian Fernandes, Juliana Gomez-Garcia, Omar Mourad, Beiping Qiang, Sara S. Nunes, Gordon Keller, Michael A. Laflamme

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsToronto General HospitalUniversity Health NetworkUniversity of Toronto
FundersCanada Research ChairsGovernment of Canada
KeywordsInduced pluripotent stem cellBioreactorMesodermCellular differentiationCell cultureHeart developmentSeedingCell growth

Abstract

fetched live from OpenAlex

Abstract Background Multiple protocols have been reported for the large-scale generation of human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) in bioreactors using small molecules; however, no comparable bioreactor-based methods have been established using growth factors. This is despite evidence that differentiation with optimized concentrations of BMP4, Activin A, and bFGF offers finer control of cardiomyocyte phenotype. Here, we develop scalable hPSC expansion and growth factor-based cardiac differentiation protocols using the vertical wheel bioreactor (VWBR) system. Methods and Results The expansion of undifferentiated hPSCs was first optimized in 100 mL VWBRs by varying parameters, including starting cell seeding density, agitation rate, and media exchange schedule. Proliferation, viability, aggregate diameter, media metabolites, and pluripotency were assessed during hPSC expansion. Next, we evaluated the effects of undifferentiated hPSC culture conditions on subsequent cardiomyocyte differentiation potential. We found that hPSCs expanded in static culture or in VWBRs at different densities and agitation rates all differentiated into hPSC-CM populations of similar cardiac purity; however, cardiomyocyte yields were initially lower when VWBR-expanded hPSCs were used. We compared the differentiation kinetics of hPSCs expanded in VWBRs to conventional 2D culture and found that the former had accelerated mesodermal commitment and significantly greater cKit + /CXCR4 + /PDGRFα - cell formation during differentiation. Modifying our aggregation and mesoderm induction steps improved cell yields and enabled reliable production of >1x10 6 cells/mL cardiac troponin T + (cTnT) hPSC-CMs. Highlighting the versatility of our growth factor-based system, variation in the BMP4:Activin A ratio enabled a second heart field-like differentiation and generation of atrial-like cardiomyocytes in VWBRs. We further show that our expansion and differentiation protocols are reproducible and economical in 500 mL VWBRs, yielding on average 1.11x10 6 hPSC-CMs/mL at a mean purity of 93% cTnT + . Characterization of VWBR produced hPSC-CM force generation, action potentials, and intercellular calcium transients confirmed the expected phenotype of ventricular-like cells. Lastly, VWBR produced hPSC-CMs robustly engrafted in the infarcted guinea pig myocardium, supporting use as a cell therapy product. Conclusions This novel bioreactor-based protocol will enable cardiac cell therapy and tissue engineering applications by providing scalable and consistent production of hPSC-derived cardiac cell products.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.019
GPT teacher head0.241
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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