GSA-Inspired Computational Nanobiosensing for Cancer Detection

We consider the cancer detection procedure (CDP) as the process of the Gravitational Search Algorithm (GSA). Nanorobots coated with protease-sensitive nanomaterials can react with protease which causes unquenching of fluorogenic probes for imaging application. As the protease concentration can induce the different degree of fluorogenic, the strength of fluorogenic can be seen as the tumor-induced biological objective function whose maximum is regarded as the tumor location. The process that employing the externally controllable and trackable nanorobots to detect the tumor in high-risk tissue is treated as using agents to complete the optimization process in the search space. To accomplish the cancer detection procedure using nanorobots with the shortest possible physiological routes and with minimal systemic exposure, it is feasible to adjust the movement of nanorobots according to the information shared by other nanorobots. Following this outline, we consider the mechanism of Gravitational Search Algorithm (GSA) which is more concise and efficient compared with PSO or GA in swarm intelligence field. Every nanorobot in the CDP can be seen as a particle in GSA and the fitness of every nanorobot is associated with the strength of its fluorogenic. To make the reality of the CDP, we should take into account the realistic in vivo propagation scenario of nanorobots swimming in the high-risk tissue to find the tumor location. Finally, we present numerical examples to demonstrate the effective of the CDP in view of GSA.