Cell migration-inspired stochastic steering strategy of magnetic particles in vascular networks

Abstract

One primary challenge of magnetic drug targeting is to achieve the efficient and accurate delivery of drug particles to the desired sites in complex physiological conditions. Though a majority of drugs are delivered through intravenous administration, until now, the kinematics and dynamics of drug particles influenced by the magnetic field, vascular topology, and blood flows are still less understood. In this work, a multi-physics dynamical model, which captures transient particle motions inside the vascular networks manipulated by the external magnetic field, is developed. Based on the model, we studied the transport efficiency of particles in the two-dimensional (2D), three-dimensional (3D) artificial, and in vivo-relevant vascular networks. It is found that particles that perform a random walk with correlated speed and persistence, recapitulating some characteristics of migratory motion of immune and metastasis cells, have the largest mean square displacements in various vascular network topologies. Next, we designed a stochastic magnetic steering strategy, using a time-varying gradient magnetic field, to manipulate particles to perform the cell migration-inspired random motions in the vasculature. The capability of the proposed steering strategy to improve the particle spreading speed and reduce the consumed magnetic energy has been demonstrated using our multi-physics numerical model. Furthermore, the influence of heterogeneous flows in the vascular networks on the particle steering efficiency was investigated. Overall, the numerical model and the proposed stochastic magnetic steering strategy can be used to assist the development of drug delivery systems for precise medicine research.