Molecular Communication Paradigm Research Articles

Enabling molecular communication through chirality of enantiomers

With the advancement of nanotechnology, there has been fervid research activity on new communication paradigms suitable for new challenging contexts, such as biological systems. Among different approaches, the most considered has been artificial Molecular Communication, where entities such as synthetic molecules, enzymes, hormones, bacteria etc. are functionalized in order to implement information exchange with the surrounding system and with other entities. In this context, it is interesting to analyze specific features that could be exploited for effective communication paradigms. In this paper, we focus on chiral molecules (a.k.a. enantiomers) as novel enablers for a molecular communication paradigm. Chirality is an interesting and appealing feature existing in nature and that can be replicated with strong emphasis in new types of materials, such as metasurfaces and metamaterials. A deep knowledge of chirality features and how chiral molecules interact with each other or with achiral molecules provides insights into designing a new molecular communication technique suitable for biological environments. In this contribution, we will highlight the main applications of chiral molecules and we will present chiral features as the viable way for realizing a nanocommunication system.

Modelling of combination therapy using implantable anticancer drug delivery with thermal ablation in solid tumor

Local implantable drug delivery system (IDDS) can be used as an effective adjunctive therapy for solid tumor following thermal ablation for destroying the residual cancer cells and preventing the tumor recurrence. In this paper, we develop comprehensive mathematical pharmacokinetic/pharmacodynamic (PK/PD) models for combination therapy using implantable drug delivery system following thermal ablation inside solid tumors with the help of molecular communication paradigm. In this model, doxorubicin (DOX)-loaded implant (act as a transmitter) is assumed to be inserted inside solid tumor (acts as a channel) after thermal ablation. Using this model, we can predict the extracellular and intracellular concentration of both free and bound drugs. Also, Impact of the anticancer drug on both cancer and normal cells is evaluated using a pharmacodynamic (PD) model that depends on both the spatiotemporal intracellular concentration as well as characteristics of anticancer drug and cells. Accuracy and validity of the proposed drug transport model is verified with published experimental data in the literature. The results show that this combination therapy results in high therapeutic efficacy with negligible toxicity effect on the normal tissue. The proposed model can help in optimize development of this combination treatment for solid tumors, particularly, the design parameters of the implant.

Anomaly Detection in Molecular Communications With Applications to Health Monitoring Networks

Early detection of diseases such as cancer plays a crucial role in their successful treatment. Motivated by this, anomaly detection in molecular nano-networks is studied. The proposed anomaly detection is, in fact, a two-tier network of artificial cells (ACs) in the first tier and a bio-cyber interface (BC) in the second tier. The ACs detect anomaly by variation in concentration of the biomarker molecules released by diseased cells (DCs) to the channel ending to ACs. This channel is modeled by a molecular communication (MC) paradigm. In the second tier, the ACs transmit a molecular message to a BC through the cardiovascular network, which is modeled again by the MC paradigm. A decision is made in the BC, which is implemented on the body skin, based on the received messages from different ACs. Due to the nature of the problem, a suboptimum design of detectors in the first and second tiers are provided. We use a Neyman-Pearson (NP) framework to analyze the detection performance of a health monitoring network. Based on bounding likelihood ratio (LR) a lower bound for the probability of detection and an upper bound for false alarm of each AC is derived. Next, taking into account the effect of ACs-BC channels, the overall performance of anomaly detection is analyzed in terms of probabilities of detection and false alarm.

Implantable Biosensor Interface Platform for Monitoring of Atherosclerosis

Drug-eluting stents have been considered to be an effective technique to reduce the severity of atherosclerotic stenosis. Recent technological advances have opened the door for developing new and innovative smart cardiovascular stents by integrating various electronic components and sensors to improve health monitoring and diagnosis. Rupture of atherosclerotic plaque represents the major cause of cardiovascular disease, such as heart attacks, due to blockages of the arterial lumen. Pentraxin-3 (PTX3) is a novel localized inflammatory biomarker associated with the development of atherosclerosis and plaque vulnerability. In this letter, we propose a biosensor interface platform for monitoring the plaque vulnerability via detection and prediction of the inflammatory biomarker (PTX3). We propose mathematical and stochastic models using a molecular communication paradigm for detection of PTX3 molecules in the atherosclerotic arterial wall using a biosensor attached to a vascular stent inside the artery. The proposed platform and models can help in the localized sensing of the atherosclerotic biomarkers for monitoring of the plaque progression and for early warning of certain disorders, such as heart attack.

Modeling of Ligand-Receptor Protein Interaction in Biodegradable Spherical Bounded Biological Micro-Environments

In this paper, we propose a generalized model for the Ligand-Receptor protein interaction in 3-D spherically bounded, diffusive biological microenvironments using molecular communication paradigm. Modeling a targeted cell as a receiver nano-machine, we derive analytical expressions for the Green’s function as well as for the expected number of the activated receptors. The molecular degradation in the environment due to enzymatic effects and the changes in pH levels are included via the first-order degradation reaction mechanism. A second-order reversible reaction mechanism is employed to model the reception process that involve the reaction of ligands to activate the receptor proteins lying on the receiver surface to form ligand-receptor complexes. We also present a particle-based simulator that incorporates the reversible reaction of molecules with the receptors present on the surface of a receiver that is located inside a bounded, 3-D microfluidic environment. Our simulations also include molecular degradation and boundary absorption of the ligands due to collision. The simulation results show perfect agreement with the results obtained from the analytical, bounded, and 3-D spherical model of the medium. The proposed models can be used for accurate prediction of the drug concentration profiles and number of activated receptors at any targeted cell.

On the Interaction between a Nanoparticulate System and the Human Body in Body Area Nanonetworks

In this work, we investigate the interaction of a nanoparticulate system for nanomedicine applications with the biological environment, i.e., the human body. Following the molecular communication paradigm, we assess how our nanoparticulate system model is suitable for coexistence in a biological environment. Specifically, we assume the presence of the human immune system that can affect the optimal behavior of nanoparticles, aiming to locally deliver drug inside the human body. When a flow of nanoparticles is injected into the blood, the interference due to the immune system can provide a strong decrease of the nanoparticle concentration, by means of “humoral immunity”, the phagocytosis process, etc. As a consequence, the correct drug delivery will occur with a lower probability. Since the mechanism behind the biological immune system is very complicated, in this paper, we start from a simplistic nanoparticulate model, where the nanoparticles and the cells of the immune system are subject to the diffusion laws. Finally, we derive the end-to-end physical model of our nanoparticulate nanomedicine system with the presence of the human immune system cells. The error analysis is then investigated in terms of how these errors can affect the performance of the system, i.e., nanoparticle survival probability.

Molecular Communication Modeling of Antibody-Mediated Drug Delivery Systems.

Antibody-mediated Drug Delivery Systems (ADDS) are emerging as one of the most encouraging therapeutic solutions for treating several diseases such as human cancers. ADDS use small molecules (antibodies) that propagate in the body and bind selectively to their corresponding receptors (antigens) expressed at the surface of the diseased cells. In this paper, the Molecular Communication (MC) paradigm, where information is conveyed through the concentration of molecules, is advocated for the engineering of ADDS and modeling their complex behavior, to provide a realistic model without the over-complication of system biology models, and the limitations of experimental approaches. The peculiarities of antibodies, including their anisotropic transport and complex electrochemical structure, are taken into account to develop an analytical model of the ADDS transport and antigen-binding kinetics. The end-to-end response of ADDS, from the drug injection to the drug absorption, is mathematically derived based on the geometry of the antibody molecule, the electrochemical structure of the antibody-antigen complex, and the physiology of the patient. The accuracy of the MC model is validated by finite-element (COMSOL) simulations. The implications of the complex interplay between the transport and kinetics parameters on the performance of ADDS are effectively captured by the proposed MC model. The MC model of ADDS will enable the discovery and optimization of drugs in a versatile, cost-efficient, and reliable manner.

Molecular Communication Noise and Capacity Analysis for Particulate Drug Delivery Systems

Particulate Drug Delivery Systems (PDDS) are ther- apeutic methods that use nanoparticles to achieve their healing effects at the exact time, concentration level of drug nanoparti- cles, and location in the body, while minimizing the effects on other healthy locations. The Molecular Communication (MC) paradigm, where the transmitted message is the drug injection process, the channel is the cardiovascular system, and the received message is the drug reception process, has been investigated as a tool to study nanoscale biological and medical systems in recent years. In this paper, the various noise effects that cause uncertainty in the cardiovascular system are analyzed, modeled, and evaluated from the information theory perspective. Analytical MC noises are presented to include all end-to-end noise effects, from the drug injection, to the absorption of drug nanoparticles by the diseased cells, in the presence of a time-varying and turbulent blood flow. The PDDS capacity is derived analytically including all these noise effects and the constraints on the drug injection. The proposed MC noise is validated by using the kinetic Monte-Carlo simulation technique. Analytical expressions of the noise and the capacity are derived, and MC is presented as a framework for the optimization of particulate drug delivery systems (PDDS). Index Terms—Drug delivery systems, nanonetworks, molecu- lar communication, time-varying channels, communication chan- nels, intra-body communication, noise modeling, capacity, kinetic Monte-Carlo.

Collision Bottleneck Throughput in Bacterial Conjugation-based Nanonetworks

Bacterial conjugation-based nanonetwork has been recently proposed as a novel molecular communication paradigm, in which the bacteria act as carriers. This is the foundational work proposing the phenomenon of collision which occurs in the form of multi-conjugation of multiple carrier bacteria at the side of receiver nanodevice. We show the effect of this conjugation-based collision on the maximum achievable throughput of the network, using a simple graph-theoretic approach, namely, Maximum Weight Bipartite Matching. One of the several interesting results that emerges concerns the maximum achievable throughput, which is bounded by Θ(n/p) in case of homogeneous nodes, where n and p refer to the total number of nodes, and the vertical layers in the network, respectively.

Antibody-based molecular communication for targeted drug delivery systems.

Antibody-based drug delivery systems (ADDS) are established as the most promising therapeutic methods for the treatment of human cancers and other diseases. ADDS are composed of small molecules (antibodies) that selectively bind to receptors (antigens) expressed by the diseased cells. In this paper, the Molecular Communication (MC) paradigm, where the delivery of molecules is abstracted as the delivery of information, is extended to be applied to the design and engineering of ADDS. The authors have previously developed a straightforward framework for the modeling of Particulate Drug Delivery Systems (PDDS) using nano-sized molecules. Here, the specificities of antibody molecules are taken into account to provide an analytical model of ADDS transport. The inputs of the MC model of PDDS are the geometric properties of the antibodies and the topology of the blood vessels where they are propagated. Numerical results show that the analytical MC model is in good agreement with finite-element simulations, and that the anisotropy is an important factor influencing ADDS.

Capacity of a Diffusion-Based Molecular Communication System With Channel Memory and Molecular Noise

Molecular Communication (MC) is a communication paradigm based on the exchange of molecules. The implicit biocompatibility and nanoscale feasibility of MC make it a promising communication technology for nanonetworks. This paper provides a closed-form expression for the information capacity of an MC system based on the free diffusion of molecules, which is of primary importance to understand the performance of the MC paradigm. Unlike previous contributions, the provided capacity expression is independent from any coding scheme and takes into account the two main effects of the diffusion channel: the memory and the molecular noise. For this, the diffusion is decomposed into two processes, namely, the Fick's diffusion and the particle location displacement, which are analyzed as a cascade of two separate systems. The Fick's diffusion captures solely the channel memory, while the particle location displacement isolates the molecular noise. The MC capacity expression is obtained by combining the two systems as function of the diffusion coefficient, the temperature, the transmitter-receiver distance, the bandwidth of the transmitted signal, and the average transmitted power. Numerical results show that a few kilobits per second can be reached within a distance range of tenth of micrometer and for an average transmitted power around 1 pW.

Calcium signaling: overview and research directions of a molecular communication paradigm

In the ongoing effort to build micro- and nanoscale machines, one of the key approaches is the bio-hybrid approach, which focuses on the use of biological constructs and engineered cells. As a natural extension of this concept to nanoscale communication, molecular communication is an umbrella term encompassing various communication systems that are built based on biological intra- and intercellular communication methods, most of which use molecules and molecular concentration as the information carrier. Compared to other proposed molecular communication systems such as diffusion-based communication and microtubular networks, calcium signaling is expected to provide a faster and more controllable system that is suitable for information dissemination and group behavior in nanoscale sensor networks. In this article, we give a general overview of calcium signaling, a novel communication paradigm that uses intercellular calcium waves in biology as a baseline, explain its capabilities, limitations, and some possible deployment scenarios. We also describe various open issues of this novel communication system and elaborate on some research directions for calcium signaling.

Molecular Communication Paradigm Overview

This paper provides an overview of the molecular communication paradigm. We first describe an architecture of molecular communication including key communication processes involved in a typical molecular communication. Characteristics and features of molecular communication are then discussed and example designs for molecular communication systems are presented. A summary of recent results in molecular communication research and future challenges are also provided.