Dynamics and Kinetics of Light-Driven Nanorobots Swarm Aggregation for Tumor Targeting

This study proposes a novel light-driven nanorobots swarm (NS) aggregation method to enhance tumor targeting efficiency. To replicate the structured and directional flow of density blood vessels near tumors, we employed a Manhattan-geometry vasculature (MGV) model, which mimics the complex, density-connected vasculature near the tumor site. This model significantly influences NS navigation and aggregation behavior, providing more realistic movement dynamics insights. We analyzed NS dynamics under light illumination, focusing on drag and thermophoretic forces. Comparisons with magnetic field-driven and non-external force strategies across three objective functions show that light-driven targeting increases efficiency by 4% to 46% and reduces targeting time by up to 27.9%. The MGV model enables precise predictions of NS movement, optimizing aggregation toward tumor tissues. These findings demonstrate the potential of light-driven NS aggregation to enhance tumor-targeting therapies, offering advantages over magnetic control in complex biological environments, with implications for photothermal therapy and precision drug delivery.