Multiscale modeling guided potency assessment of mRNA-lipid nanoparticles.

mRNA lipid nanoparticle (mRNA-LNP) technology has emerged as a cornerstone in vaccine development due to its high delivery efficiency, molecular stability, and favorable safety profile. However, rapid and reliable potency assessment remains challenging because of limited mechanistic understanding of delivery processes and sparse experimental data. To address these gaps, we introduce a mechanism-informed, multi-scale kinetic modularized modeling framework that quantitatively captures the coupled dynamics of mRNA delivery across nanoparticle, cellular, and macroscopic scales. The model incorporates variability in LNP-cell interactions and integrates key determinants, such as dosage, LNP and cell size distributions, cell proliferation, and membrane properties-factors that critically shape delivery efficiency and response heterogeneity. Its cell-based architecture and modular design enable adaptability to diverse delivery systems and physiological contexts. By leveraging advanced multi-omics assays, including single-molecule fluorescent in situ hybridization (smFISH) for single-cell resolution of mRNA and protein expression, our framework provides mechanistically grounded modeling and robust prediction of therapeutic potency, offering a powerful platform for optimizing mRNA-based interventions.