A novel scheme for nanoparticle steering in blood vessels using a functionalized magnetic field.

Magnetic drug targeting is a drug delivery approach in which therapeutic magnetizable particles are injected, generally into blood vessels, and magnets are then used to guide and concentrate them in the diseased target organ. Although many analytical, simulation, and experimental studies on capturing schemes for drug targeting have been conducted, there are few studies on delivering the nanoparticles to the target region. Furthermore, the sticking phenomenon of particles to vessels walls near the injection point, and far from the target region, has not been addressed sufficiently. In this paper, the sticking issue and its relationship to nanoparticle steering are investigated in detail using numerical simulations. For wide ranges of blood vessel size, blood velocity, particle size, and applied magnetic field, three coefficient numbers are uniquely generalized: vessel elongation, normal exit time, and force rate. With respect these new parameters, we investigated particle distribution trends for a Y-shaped channel and computed ratios of correctly guided particles and particles remaining in the vessel. We found that the sticking of particles to vessels occurred because of low blood flow velocity near the vessel walls, which is the main reason for low targeting efficiency when using a constant magnetic gradient. To reduce the sticking ratio of nanoparticles, we propose a novel field function scheme that uses a simple time-varying function to separate the particles from the walls and guide them to the target point. The capabilities of the proposed scheme were examined by several simulations of both Y-shaped channels and realistic three-dimensional (3-D) model channels extracted from brain vessels. The results showed a significant decrease in particle adherence to walls during the delivery stage and confirmed the effectiveness of the proposed magnetic field function method for steering nanoparticles for targeted drug delivery.