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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.17090 |
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| _version_ | 1866911524603297792 |
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| author | Cheng, Fuqiang Jahromi, Zahra Foroozan Wang, Keqi Caldwell, Thomas C. Cai, Grace Choy, Keilung Auclair, Jared Campbell, Jeffrey L. Zhao, Youbo Yoon, Seongkyu Harcum, Sarah W. Xie, Wei |
| author_facet | Cheng, Fuqiang Jahromi, Zahra Foroozan Wang, Keqi Caldwell, Thomas C. Cai, Grace Choy, Keilung Auclair, Jared Campbell, Jeffrey L. Zhao, Youbo Yoon, Seongkyu Harcum, Sarah W. Xie, Wei |
| contents | Scalable manufacturing of human induced pluripotent stem cells (iPSCs) is essential for industrial-scale production of cell therapies and regenerative medicines. However, the 3D aggregate cultures used in manufacturing exhibit substantial spatial and metabolic heterogeneity compared with the relatively homogeneous monolayer systems used in laboratory studies, complicating mechanistic understanding and predictive metabolic modeling across culture scales. To address this challenge, we developed a modular multiscale mechanistic foundation model that links molecular, cellular, and macroscopic processes while accounting for spatial and metabolic heterogeneity. The framework integrates extracellular culture dynamics, intracellular metabolic fluxes, and cellular redox states by extending a previously established monolayer kinetic network and coupling it with a biological systems-of-systems (Bio-SoS) multiscale model for aggregate cultures, incorporating explicit redox interactions. Systematic monolayer and aggregate experiments (including multiple isotopic tracers, extracellular metabolite profiling, and two-photon optical redox imaging) were used to improve and validate the model. This integrated framework unifies heterogeneous datasets across culture configurations and enables mechanistic interpretation of metabolic and redox responses across heterogeneous culture scales, providing a quantitative foundation for scalable iPSC biomanufacturing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_17090 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Intracellular Measurement-Informed Multiscale Modeling for Scalable iPSC Manufacturing Cheng, Fuqiang Jahromi, Zahra Foroozan Wang, Keqi Caldwell, Thomas C. Cai, Grace Choy, Keilung Auclair, Jared Campbell, Jeffrey L. Zhao, Youbo Yoon, Seongkyu Harcum, Sarah W. Xie, Wei Cell Behavior Scalable manufacturing of human induced pluripotent stem cells (iPSCs) is essential for industrial-scale production of cell therapies and regenerative medicines. However, the 3D aggregate cultures used in manufacturing exhibit substantial spatial and metabolic heterogeneity compared with the relatively homogeneous monolayer systems used in laboratory studies, complicating mechanistic understanding and predictive metabolic modeling across culture scales. To address this challenge, we developed a modular multiscale mechanistic foundation model that links molecular, cellular, and macroscopic processes while accounting for spatial and metabolic heterogeneity. The framework integrates extracellular culture dynamics, intracellular metabolic fluxes, and cellular redox states by extending a previously established monolayer kinetic network and coupling it with a biological systems-of-systems (Bio-SoS) multiscale model for aggregate cultures, incorporating explicit redox interactions. Systematic monolayer and aggregate experiments (including multiple isotopic tracers, extracellular metabolite profiling, and two-photon optical redox imaging) were used to improve and validate the model. This integrated framework unifies heterogeneous datasets across culture configurations and enables mechanistic interpretation of metabolic and redox responses across heterogeneous culture scales, providing a quantitative foundation for scalable iPSC biomanufacturing. |
| title | Intracellular Measurement-Informed Multiscale Modeling for Scalable iPSC Manufacturing |
| topic | Cell Behavior |
| url | https://arxiv.org/abs/2603.17090 |