Intracellular Measurement-Informed Multiscale Modeling for Scalable iPSC Manufacturing

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.

Figures (19)

• Figure 1: Cell growth, glucose, lactate, and ammonia profiles and rates for Historic Static, Static Pyruvate, and Aggregate culture conditions. (A) Viable cell density (VCD) profiles. (B) Specific growth rates. (C) Glucose concentration profiles. (D) Specific glucose consumption rates. (E) Lactate concentration profiles. (F) Specific lactate production rates. (G) Ammonia concentration profiles. (H) Specific ammonia production rates. Error bars represent the standard deviation across biological replicates. For clarity, data points corresponding to Historic Static conditions are slightly shifted to the left of each sampling time, whereas Static Pyruvate conditions are slightly shifted to the right to facilitate visual distinction of overlapping measurements.
• Figure 2: Glutamine, glutamate, and alanine profiles and rates for Historic Static, Static Pyruvate, and Aggregate culture conditions. (A) Glutamine concentration profiles. (B) Specific glutamine consumption rates. (C) Glutamate concentration profiles. (D) Specific glutamate production rates. (E) Alanine concentration profiles. (F) Specific alanine production rates. Error bars represent the standard deviation across biological replicates. For clarity, data points corresponding to Historic Static conditions are slightly shifted to the left of each sampling time, whereas Static Pyruvate conditions are slightly shifted to the right to facilitate visual distinction of overlapping measurements.
• Figure 3: Metabolic network for iPSC including regulatory reactions. Intracellular metabolites are shown in blue, while extracellular metabolites are shown in green and denoted with an "E" prefix. Reaction fluxes are represented by black arrows, with transport reactions connecting intracellular and extracellular species. Energy-generating steps are highlighted in purple, whereas energy-consuming steps are indicated in orange. Oxidative phosphorylation in the mitochondria, associated with NADH oxidation and oxygen consumption, is indicated by the green star. Reactions involving NAD$^{+}$/NADH and FAD/FADH$_2$ are explicitly annotated to capture cellular redox balance. The network integrates glycolysis, the TCA cycle, oxidative phosphorylation, amino acid metabolism, and biomass synthesis. EPYR in Static Pyruvate culture represents both labeled and unlabeled extracellular pyruvate.
• Figure 4: Intracellular MID data for the Static Pyruvate HGLL culture condition at 48 h. MID data were corrected for natural isotopic abundance. Metabolite abbreviations are: PYR (pyruvate), LAC (lactate), ALA (alanine), CIT (citrate), ASP (aspartate), and ASN (asparagine). A complete list of abbreviations is provided in Supplementary Materials Table S1. The intracellular MIDs for the LGLL, HGLL, and LGHL static pyruvate cultures are provided in the Supplementary Materials (Fig. S1-S3).
• Figure 5: Aggregate growth, size distribution, and redox dynamics of iPSC aggregate cultures. (A) Representative brightfield images of iPSC aggregates from Day 1 to Day 5 illustrating aggregate growth and morphological evolution over time. The scale bar (bottom right) corresponds to 1000 $\mu$m. (B) Violin plots showing the distribution of iPSC aggregate sizes across five days of culture. Green violins represent the kernel density of aggregate size measurements at each time point. Red horizontal bars denote the mean aggregate size, while gray horizontal bars indicate the median. Gray vertical bars and whiskers show the minimum and maximum observed aggregate sizes. Day 3 corresponds to measurements taken prior to feeding, and aggregate size distributions were similar before and after feeding. (C) Total aggregate counts measured from Day 1 to Day 5. (D) Distribution of redox ratios measured in aggregate cultures from Day 0 to Day 5 using the TPE sensor. Boxplots show the median and interquartile range, with whiskers indicating the full data range; individual replicate measurements are overlaid as points. (E) Temporal trends in redox ratios measured by a non-destructive TPE-based method, FAD/(FAD+NAD(P)H), and by an offline enzymatic assay, NAD$^+$/ (NAD$^+$+NADH), demonstrating consistent redox dynamics across measurement modalities. The TPE-based values represent averages calculated over both the measurement period and the analyzed cell population.