HYBRID SWARM INTELLIGENCE ALGORITHM FOR NANOCARRIERS TARGETING CANCER CELLS

摘要

Recent advances in nanotechnology and swarm intelligence offer new possibilities to the targeted elimination of cancerous cells. Swarm intelligence, which refers to the collective problem solving of a group of individuals, can be used in locating cancer regions. It has been recently shown that magnetic and fluorescent nanocarriers are capable of binding to molecules unique to the surfaces of cancer cells. Furthermore, the transport of these nanocarriers into the nuclei has been proven to damage the DNA, resulting in an arrest of cytokinesis in cancer cells. In this paper, we develop a hybrid swarm intelligence algorithm by combining and simplifying two existing swarm intelligence algorithms such that they can be easily implemented in nanocarriers. The targeting process uses the attract-repel swarm intelligence algorithm to randomly swarm and eventually locate the general area of the cancer cells. Then the chemical binding of aptamers is made more effective by switching to a simplified version of Kennedy's particle swarm intelligence (PSO) algorithm to target the cancerous cell. We develop a detailed simulation model that can detect and destroy multiple targeted cells and regions. Our enhanced swarm intelligence algorithm can not only be used in targeted cancer treatment but is also applicable to any form of payload delivery where the target position is not known in advance.