A closer look at nature has recently brought more interest in exploring and utilizing intra-body communication networks composed of cells as intrinsic, perfectly biocompatible infrastructures to deliver therapeutics. Naturally occurring cell-to-cell communication systems are being manipulated to release, navigate, and take-up soluble cell-derived messengers that are either therapeutic by nature or carry therapeutic molecular cargo. One example of such structures is extracellular vesicles (EVs) which have been recently proven to have pharmacokinetic properties, opening new avenues for developing the next generation biotherapeutics. In this paper, we study theoretical aspects of the EV transfer within heart tissue as a case study by utilizing an information and communication technology-like approach in analyzing molecular communication systems. Our modeling implies the abstraction of the EV releasing cells as transmitters, the extracellular matrix as the channel, and the EV receiving cells as receivers. Our results, derived from the developed analytical models, indicate that the release can be modulated using external forces such as electrical signals, and the transfer and reception can be affected by the extracellular matrix and plasma membrane properties, respectively. The presented modeling provides initial results for the EV biodistributions and contribute to avoiding unplanned administration, often resulting in side- and adverse effects.

In this paper, we design a drug release mechanism for dynamic time division multiple access (TDMA)-based molecular communication via diffusion (MCvD) in case of having multiple transmitter units and a single receiver. In the proposed scheme, the communication frame is divided into several time slots in which a transmitter nanomachine is scheduled to convey its information by releasing the molecules into the medium. To optimize the number of released molecules and the time duration of each time slot (symbol duration), we formulate multi-objective optimization problems whose objective functions are the bit error rate (BER) of each transmitter nanomachine. Based on the number of released molecules and symbol durations, we consider four cases, namely: “fixed-time fixed-number of molecules” (FTFN)“, fixed-time varying-number of molecules” (FTVN)“, varying-time fixed-number of molecules” (VTFN), and “varying-time varying-number of molecules” (VTVN). For the channel model, we consider a 3-dimensional diffusive environment with drift in three directions. Simulation results show that the FTFN approach is the least complex one with BER around 10-2, but, the VTVN is the most complex scenario with the BER around 10-8.

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.

Multiple access-based molecular communication (MC) is an important way to implement MC nanonetworks for the Internet of Bio-Nano Things. In this paper, we propose a framework for time division multiple access (TDMA)-based MC by considering multiple-type transmission multiple-type reception (MTMR) for a system with multiple transmitter nanomachines and one receiver nanomachine (RN) which is non-ideal and has a switching delay. The reception process is based on ligand-binding reception. We study the drug release management approaches by minimizing the error probability. Besides, we propose a metric to find signal-to-interference ratio based on the channel memory. Analytical results, which are verified by the simulation, show that the TDMA-MTMR MC outperforms the state-of-the-art TDMA framework.

Anomalous diffusion of extracellular vesicles (EVs) occurs because of the natural stiffness and stress relaxation of the extracellular matrix (ECM). This phenomenon has not been considered so far in attempts of computational modeling of the biodistribution of EVs, which is used as a powerful tool in pre-clinical and clinical practice. Here we present a novel model of the anomalous EV diffusion based on a 3-dimensional partial differential equation from the molecular communications theory, and solve it using the Green’s function theorem. We also verify our analytical results using a particle-based simulation (PBS). The model encompasses a source function for the EV release from cells, their degradation through natural half-life, and extracellular binding. Our findings reveal that different anomalous schemes lead to various propagation patterns and can be used for providing insights into designing EV-based drug delivery systems.

The limited storage capacity at the transmitters of a molecular communication (MC) system can affect the system’s performance. One of the reasons for this limitation is the size restriction of the transmitter, which the storage must be replenished so that the transmitter has enough molecules for future transmission. This paper proposes a biologically inspired transmitter model based on neurons for MC whose storage charging and discharging follow differential equations. The proposed transmitter opens its outlet for a specific time in each time frame to exponentially release a portion of stored molecules to code bit-1 and remains silent to code bit-0. We analyze our model based on different transmission parameters. These parameters are the symbol duration, the release time duration, the storage capacity, and the release and replenishment rate of the storage. We find that the storage outlet must be open for a certain period within the time slot duration in order to improve the performance of the proposed system. Additionally, we demonstrate that determining the effect of storage capacity size can be important for practical MC due to the significant differences between the ideal transmitter and the proposed one, which have a limited size. We show that increases in the transmitter storage size can improve the system performance. As a result, taking a closer look at these practical transmitters is essential to solving the problems and challenges of molecular communication systems.