Reduced-order modeling of solute transport within physiologically realistic solid tumor microenvironment

Solid tumors are characterized by densely packed extracellular matrices and limited vascularization, creating significant resistance to both diffusive and convective transport. In this study, we developed an integration of numerical computations with a theoretical modeling framework that couples three phase viscous-laminar transient simulations of glycocalyx-patched tumor vessel resolving plasma, red blood cells (RBCs), and white blood cells (WBCs) and tracking their volume fractions to a calibrated reverse advection-diffusion (RAD) model for intratumoral plasma transport. The reduced-order tumor microenvironment model uses histology-informed extracellular matrix (ECM) tumor domain and packing fraction, together with explicit glycocalyx-patch electrohydrodynamics (EHD) at the tumor vessel wall. At the fenestra, EHD increases inlet plasma intensity relative to a non-EHD framework across all models (means: 0.576 non-EHD vs 0.722 EHD; gain 25.34%). Numerical simulations of plasma perfusion in both the tumor ECM domain and a microfluidic benchmark exhibit two-stage kinetics, with an initial advection-dominated regime. The RAD model reproduces this behavior and, after a simple temporal calibration to account for pore-scale hydrodynamic acceleration resolved by computational fluid dynamics (CFD), matches the observed propagation. By using fully resolved, EHD-inclusive multiphase CFD simulations to calibrate a reduced-order RAD model parameterized by measurable geometric features, we bridge the gap between classical Darcy–Starling tissue perfusion models and fully resolved CFD. The resulting framework provides a tractable, mechanism-grounded tool for quantifying plasma progression in dense solid tumors.