Autonomous In Vivo Computation in Internet of Nano Bio Things

Abstract

Different natural biological processes are possible because of the collaboration among simple living cells. Similarly computerized systems such as multi-agent systems (MAS) rely on multiple interacting agents with simplified and reduced capability, to collectively solve difficult problems that are impossible for individual agents to solve on their own. This work highlights an autonomous tumor sensitization strategy in complex human vasculature, where target detection is achieved through swarm coordination mechanism, with no prior knowledge of tumor location. We propose that small-scale biocompatible organisms such as nanoparticles, can perform deterministic tasks following the simple principles of aggregation and migration. We aim to show through computational experiments that tumor-triggered bio-physical gradients can be leveraged by nanoparticles to collectively move towards the potential tumor hypoxic regions. Although individual nanoparticles have no target-directed locomotion ability due to limited communication and computation capability, we demonstrate that once passive collaboration is achieved, they can successfully avoid obstacles and detect the tumor. Numerical experiments demonstrate that the overall targeting efficiency could improve considerably from 10% to 90% through passive collaboration among nanoparticles. Furthermore, with the introduction of noisy search space and mobile obstacles, the targeting performance would reduce by 25%. Such self-regulating particles can be used as homing agents for target amplification, and hence can assist in early cancer detection through contrast-enhanced medical imaging. We believe that our work will motivate self-dependent and non-centralized approach for magnification of tumor location.