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Intracellular Measurement-Informed Multiscale Modeling for Scalable iPSC Manufacturing.

Fuqiang Cheng1, Zahra Foroozan Jahromi2, Keqi Wang1

  • 1Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA.

Arxiv
|March 30, 2026
PubMed
Summary
This summary is machine-generated.

Scalable manufacturing of human induced pluripotent stem cells (iPSCs) requires understanding 3D culture heterogeneity. A new multiscale model links molecular, cellular, and macroscopic processes for predictive metabolic modeling in iPSC biomanufacturing.

Keywords:
Advanced Optical SensingCellular Metabolic–Redox ModelingCulture Spatiotemporal HeterogeneityMonolayer and Aggregate CulturesMulti-Scale Mechanistic ModelingMultiple Isotope Labelinginduced Pluripotent Stem Cells

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Area of Science:

  • Biotechnology and Bioprocessing
  • Stem Cell Biology
  • Metabolic Engineering

Background:

  • Scalable manufacturing of human induced pluripotent stem cells (iPSCs) is critical for cell therapies.
  • Existing 3D aggregate cultures show spatial and metabolic heterogeneity, hindering mechanistic understanding and predictive modeling.
  • Laboratory-scale monolayer systems are more homogeneous but do not fully represent manufacturing conditions.

Purpose of the Study:

  • To develop a multiscale mechanistic model for human induced pluripotent stem cells (iPSCs) that accounts for spatial and metabolic heterogeneity in 3D aggregate cultures.
  • To link molecular, cellular, and macroscopic processes for improved mechanistic understanding and predictive metabolic modeling.
  • To provide a quantitative foundation for scalable iPSC biomanufacturing.

Main Methods:

  • Developed a modular multiscale mechanistic foundation model integrating extracellular dynamics, intracellular metabolic fluxes, and cellular redox states.
  • Extended a monolayer kinetic network and coupled it with a biological systems-of-systems (Bio-SoS) multiscale model for aggregate cultures.
  • Utilized systematic experiments including isotopic tracers, metabolite profiling, and two-photon optical redox imaging for model validation.

Main Results:

  • The integrated framework successfully unified heterogeneous datasets across different culture configurations (monolayer and aggregate).
  • The model enabled mechanistic interpretation of metabolic and redox responses in heterogeneous iPSC cultures.
  • Demonstrated the capability to predict and understand metabolic behavior across various culture scales.

Conclusions:

  • The developed multiscale model provides a quantitative foundation for understanding and optimizing scalable iPSC biomanufacturing.
  • Accounting for spatial and metabolic heterogeneity is crucial for accurate modeling of iPSC aggregate cultures.
  • This approach facilitates the advancement of cell therapies and regenerative medicines through improved manufacturing processes.