CRISPR-Enabled Graphene-Based Bio-Cyber Interface Model for In Vivo Monitoring of Non-Invasive Therapeutic Processes

In this paper, we present a model of the bio-cyber interface for the Internet of Bio-Nano Things application. The proposed model is inspired by the gains of integrating the Clustered Regularly Interspace Short Palindromic Repeats (CRISPR) technology with the Graphene-Field effect transistor (GFET). The capabilities of the integrated system are harnessed to detect nucleic acids transcribed by another component of the bio-cyber interface, a bioreporter, on being exposed to the signalling molecule of interest. The proposed model offers a label-free real-time signal transduction with multi-symbol signalling capability. We model the entire operation of the interface as a set of simultaneous differential equations representing the process's kinetics. The solution to the model is obtained using a numerical method. Numerical results show that the performance of the interface is influenced by parameters such as the concentrations of the input signalling molecules, the surface receptor on the bioreporter, and the CRISPR complex. The interface's performance also depends considerably on the elimination rate of the signalling molecules from the body. For multi-symbol molecular signalling, the rate of degradation of the transcribed RNAs influences the system's susceptibility to inter-symbol interference.