Information-Theoretic Model and Analysis of Molecular Signaling in Targeted Drug Delivery

Targeted Drug Delivery for Cardiovascular Disease: Modeling of Modulated Extracellular Vesicle Release Rates

Invasive and medical therapy has led to major improvements in cardiovascular disease management, but important challenges remain open. The discovery of a nano-sized system of extracellular vesicles (EVs) is opening new possibilities for reprogramming malfunctioning cells and indicates that EVs can be employed in therapeutic biomedical applications as engineered drug vehicles. Molecular communication (MC) has applications for treating cells with directed drug delivery, employing special targeting transmembrane proteins. In this paper, we propose a novel drug delivery system for cardiovascular diseases using an EV-mediated MC platform and exemplify the potential use in hypertrophic cardiomyopathy. We utilize intracellular calcium signaling as a natural mediator of EVs released from synthetic cells and model the release rate. We propose to use the cells as a therapeutic release system with a control signal input which modulates the EVs release rate as the output signal. We also study the frequency domain of the proposed model and estimate the transfer function of the therapeutic release system model numerically where the root-mean-square error for two separate estimated output signals are 0.0353 and 0.0124. The proposed EV-mediated targeted drug delivery system can make breakthroughs in future healthcare, in cardiovascular and other diseases where targeting is required.

A Voxel Model to Decipher the Role of Molecular Communication in the Growth of Glioblastoma Multiforme

Glioblastoma Multiforme (GBM), the most malignant human tumour, can be defined by the evolution of growing bio-nanomachine networks within an interplay between self-renewal (Grow) and invasion (Go) potential of mutually exclusive phenotypes of transmitter and receiver cells. Herein, we present a mathematical model for the growth of GBM tumour driven by molecule-mediated inter-cellular communication between two populations of evolutionary bio-nanomachines representing the Glioma Stem Cells (GSCs) and Glioma Cells (GCs). The contribution of each subpopulation to tumour growth is quantified by a voxel model representing the end to end inter-cellular communication models for GSCs and progressively evolving invasiveness levels of glioma cells within a network of diverse cell configurations. Mutual information, information propagation speed and the impact of cell numbers and phenotypes on the communication output and GBM growth are studied by using analysis from information theory. The numerical simulations show that the progression of GBM is directly related to higher mutual information and higher input information flow of molecules between the GSCs and GCs, resulting in an increased tumour growth rate. These fundamental findings contribute to deciphering the mechanisms of tumour growth and are expected to provide new knowledge towards the development of future bio-nanomachine-based therapeutic approaches for GBM.

Efficient Framework Analysis for Targeted Drug Delivery Based on Internet of Bio-NanoThings

The Internet of Bio-NanoThings (IoBNTs) is a novel paradigm that derives from synthetic biology and advances in nanotechnology for controlling the embedded nanodevices in various medical applications. However, numerous studies have focused on communication efficiency among the nanodevices in a given network, the challenges such as the design and the development of the nanodevices, and the coordination of molecular communication within the wireless body area network (BAN), and the interface connection between the BAN and the Internet are yet to be addressed. Therefore, in this study, we present a framework analysis comprising of the compartmental model, for studying the effects and variances in drug concentration that occur inside intra-body nanonetworks through IoBNT, while taking into account the properties of target cells as well as the ligand-receptor binding mechanism. A performance analysis of the proposed framework for the forward link (i.e., from the Internet to the intra-body nanonetwork) and reverse link (i.e., from the intra-body nanonetwork to the Internet) is presented. The simulation results of the developed framework reveal its ability to enhance the delivery of therapeutic drugs to the target cell while minimizing the side effects in healthy cells.