Intracellular Measurement-Informed Multiscale Modeling for Scalable iPSC Manufacturing

TL;DR

This paper presents a multiscale mechanistic model that integrates intracellular, extracellular, and spatial heterogeneity data to improve understanding and prediction of iPSC culture dynamics for scalable manufacturing.

Contribution

It introduces a modular multiscale model linking molecular, cellular, and macroscopic processes, validated with experimental data, to enhance predictive capabilities in iPSC biomanufacturing.

Findings

Model accurately predicts metabolic fluxes in aggregate cultures

Experimental validation confirms model's ability to interpret redox responses

Framework unifies heterogeneous datasets across culture scales

Abstract

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.