Revolutionizing Stroke Research: 3D Neurovascular Unit Models for Pharmacodynamic Prediction

Background: Ischemic stroke is a major cause of disability and death. Understanding microscale pathophysiology within neurovascular units (NVUs) is critical for developing therapies, yet traditional methods struggle with spatiotemporal heterogeneity. In silico modeling offers a solution for multiscale analysis. Objective: To develop a 3D in silico model of ischemic stroke integrating NVU morphology, Monte Carlo dynamics, cellular automata, and pharmacodynamics to predict lesion evolution and assess treatments. Methods: We created a hybrid 3D model featuring: anatomically detailed NVUs; Monte Carlo simulation of oxygen diffusion; cellular automata for cell viability/death rules; a pharmacodynamic module for drug effects. The model was calibrated with in vitro and in vivo (rat) data. Results: The model replicates: penumbra and infarct core formation (matching experiments); hypoxia and energy deficit gradients in NVUs; neuroprotective drug effects by timing/dose. Sensitivity analysis identified key parameters driving penumbra to necrosis transition. Conclusion: This 3D in silico platform enables: studying ischemic mechanisms at the NVU level; predicting pharmacotherapy efficacy; optimizing preclinical experiments; studying ischemic injury mechanisms at the NVU level, accounting for stochasticity and discreteness of processes; predicting the efficacy of pharmacotherapeutic interventions in silico; optimizing preclinical experiment design. The model can serve as a tool for personalizing stroke therapy by simulating individual perfusion parameters and pharmacokinetics.