Over the past 10 years, molecular communication (MC) has established itself as a key transformative paradigm in communication theory. Inspired by chemical communications in biological systems, the focus of this discipline is on the modeling, characterization, and engineering of information transmission through molecule exchange, with immediate applications in biotechnology, medicine, ecology, and defense, among others. Despite a plethora of diverse contributions, which has been published on the subject by the research community, a general framework to study the performance of MC systems is currently missing. This paper aims at filling this gap by providing an analysis of the physical processes underlying MC, along with their information-theoretic underpinnings. In particular, a mathematical framework is proposed to define the main functional blocks in MC, supported by general models from chemical kinetics and statistical mechanics. In this framework, the Langevin equation is utilized as a unifying modeling tool for molecule propagation in MC systems, and as the core of a methodology to determine the information capacity. Diverse MC systems are classified on the basis of the processes underlying molecule propagation, and their contribution in the Langevin equation. The classifications and the systems under each category are as follows: random walk (calcium signaling, neuron communication, and bacterial quorum sensing), drifted random walk (cardiovascular system, microfluidic systems, and pheromone communication), and active transport (molecular motors and bacterial chemotaxis). For each of these categories, a general information capacity expression is derived under simplifying assumptions and subsequently discussed in light of the specific functional blocks of more complex MC systems. Finally, in light of the proposed framework, a roadmap is envisioned for the future of MC as a discipline.

Synthetic biology, through genetic circuit engineering in biological cells, is paving the way towards the realization of programmable man-made living devices, able to naturally operate within normally less accessible domains, i.e., the biological and the nanoscale. The control of the information processing and exchange between these engineered-cell devices, based on molecules and biochemical reactions, i.e., Molecular Communication (MC), will be enabling technologies for the emerging paradigm of the Internet of Bio-Nano Things, with applications ranging from tissue engineering to bioremediation. In this paper, the design of genetic circuits to enable MC links between engineered cells is proposed by stemming from techniques for information coding, and inspired by recent studies favoring the efficiency of analog computation over digital in biological cells. In particular, the design of a joint encoder-modulator for the transmission of binary-modulated molecule concentration is coupled with a decoder that computes the a-posteriori log-likelihood ratio of the information bits from the propagated concentration. These functionalities are implemented entirely in the biochemical domain through activation and repression of genes, and biochemical reactions, rather than classical electrical circuits. Biochemical simulations are used to evaluate the proposed design against a theoretical encoder/decoder implementation taking into account impairments introduced by diffusion noise.

The design of communication systems capable of processing and exchanging information through molecules and chemical processes is a rapidly growing interdisciplinary field, which holds the promise to revolutionize how we realize computing and communication devices. While molecular communication (MC) theory has had major developments in recent years, more practical aspects in designing components capable of MC functionalities remain less explored. This paper designs chemical reactions-based microfluidic devices to realize binary concentration shift keying (BCSK) modulation and demodulation functionalities. Considering existing MC literature on information transmission via molecular pulse modulation, we propose a microfluidic MC transmitter design, which is capable of generating continuously predefined pulse-shaped molecular concentrations upon rectangular triggering signals to achieve the modulation function. We further design a microfluidic MC receiver capable of demodulating a received signal to a rectangular output signal using a thresholding reaction and an amplifying reaction. Our chemical reactions-based microfluidic molecular communication system is reproducible and its parameters can be optimized. More importantly, it overcomes the slow-speed, unreliability, and non-scalability of biological processes in cells. To reveal design insights, we also derive the theoretical signal responses for our designed microfluidic transmitter and receiver, which further facilitate the transmitter design optimization. Our theoretical results are validated via simulations performed through the COMSOL Multiphysics finite element solver. We demonstrate the predefined nature of the generated pulse and the demodulated rectangular signal together with their dependence on design parameters.

Hundreds of millions of people worldwide are affected by viral infections each year, and yet, several of them neither have vaccines nor effective treatment during and post-infection. This challenge has been highlighted by the COVID-19 pandemic, showing how viruses can quickly spread and impact society as a whole. Novel interdisciplinary techniques must emerge to provide forward-looking strategies to combat viral infections, as well as possible future pandemics. In the past decade, an interdisciplinary area involving bioengineering, nanotechnology and information and communication technology (ICT) has been developed, known as Molecular Communications. This new emerging area uses elements of classical communication systems to molecular signalling and communication found inside and outside biological systems, characterizing the signalling processes between cells and viruses. In this paper, we provide an extensive and detailed discussion on how molecular communications can be integrated into the viral infectious diseases research, and how possible treatment and vaccines can be developed considering molecules as information carriers. We provide a literature review on molecular communications models for viral infection (intra-body and extra-body), a deep analysis on their effects on immune response, how experimental can be used by the molecular communications community, as well as open issues and future directions.

Information transmission and storage have gained traction as unifying concepts to characterize biological systems and their chances of survival and evolution at multiple scales. Despite the potential for an information-based mathematical framework to offer new insights into life processes and ways to interact with and control them, the main legacy is that of Shannon’s, where a purely syntactic characterization of information scores systems on the basis of their maximum information efficiency. The latter metrics seem not entirely suitable for biological systems, where transmission and storage of different pieces of information (carrying different semantics) can result in different chances of survival. Based on an abstract mathematical model able to capture the parameters and behaviors of a population of single-celled organisms whose survival is correlated to information retrieval from the environment, this paper explores the aforementioned disconnect between classical information theory and biology. In this paper, we present a model, specified as a computational state machine, which is then utilized in a simulation framework constructed specifically to reveal emergence of a “subjective information”, i.e., trade-off between a living system’s capability to maximize the acquisition of information from the environment, and the maximization of its growth and survival over time. Simulations clearly show that a strategy that maximizes information efficiency results in a lower growth rate with respect to the strategy that gains less information but contains a higher meaning for survival.