Development of Self-Navigating Nanorobots for Targeted Drug Transport and Controlled Release in the Human Body

Abstract

Untargeted systemic drug administration and even passively targeted nanocarriers remain fundamentally limited by their inability to actively navigate the complex, branching, flow-dominated architecture of the human vasculature. This paper presents a system architecture and simulation-based evaluation framework for self-navigating nanorobots capable of autonomous, closed-loop transport from an injection site to a specific lesion — such as a tumor, thrombus, or atherosclerotic plaque — followed by docking and controlled drug release. The proposed nanorobot integrates a helical flagellar or magnetically responsive propulsion unit, an onboard AI sensing-control node, a drug payload reservoir with a stimuli-gated release port, and surface receptors for terminal target recognition. Navigation is achieved through a closed loop combining external real-time imaging-based localization (e.g., magnetic resonance or photoacoustic tracking), a reinforcement-learning path-planning policy that incorporates a patient-specific vascular roadmap, and an external rotating-field actuation system that steers the nanorobot while continuously replanning around detected obstacles such as vessel bifurcations, immune cells, or existing plaque. We describe the propulsion physics, control architecture, and a physiologically parameterized simulation environment used to train and evaluate the navigation policy. Simulated results show that the proposed autonomous system achieves an approximately 89% target-zone arrival rate and a mean time-to-target of approximately 24 minutes, compared with 33–39% arrival rates and 95–110 minute transit times for open-loop magnetic or purely chemically propelled baselines — an approximate 75% reduction in transit time. We discuss propulsion physics at low Reynolds number, biocompatibility and clearance of onboard components, external field safety limits, regulatory classification as an active implantable/combination device, and a staged translational roadmap from simulation to microfluidic and in vivo validation. This work is intended to provide a reusable design, control, and evaluation framework for future research in autonomous medical microrobotics.