Computational Studies of Controlled Nanoparticle Agglomerations for MRI-Guided Nanorobotic Drug-Delivery Systems

Magnetic Resonance Imaging (MRI) guided nanorobotic systems that could perform diagnostic, curative and reconstructive treatments in the human body at the cellular and sub-cellular level in a controllable manner have recently been proposed. The concept of a MRI-guided nanorobotic system is based on the use of a MRI scanner to induce the required external driving forces to guide magnetic nanocapsules to a specific target. However, the maximum magnetic gradient specifications of existing clinical MRI systems are not capable of driving superparamagnetic nanocapsules against the blood flow and therefore these MRIs do not allow for navigation. The present paper proposes a way to overcome this critical drawback through the formation of micron size agglomerations where their size can be regulated by external magnetic stimuli. This approach is investigated through modeling of the physics that govern the self-assembly of the nanoparticles. Additionally a computational tool has been developed that incorporates the derived models and performs simulation, visualization and post-processing analysis. Preliminary simulation results demonstrate that external magnetic field causes aggregation of nanoparticles while they flow in the vessel. This is a promising result — in accordance with similar experimental results — and encourages further investigation on the nanoparticle based self-assembly structures for use in nanorobotic drug delivery.