Nanomedicine is an attempt to revolutionize current methods for diagnosing, treating and preventing diseases that integrates fields such as molecular biology, biotechnology as well as nanotechnology. One envisioned application is sensing and actuation capabilities at the molecular scale using nano scale devices, namely nanomachines. While numerous examples of these applications have been tested in vivo, the real deployments are far from reality. This is mainly due to limitations in controlling as well as monitoring their performance. At the same time, the miniature scale of nanomachines means their computational capabilities are also limited. However, integrating communication and networking functionalities can provide new opportunities for sensing and actuation applications of nanomachines. One form of communication that has been recently appointed to realise this vision is Molecular Communication. Many natural molecular communication systems are found inside the human body. The current challenge is to utilise these natural systems to create artificial biocompatible communication networks that can interconnect multiple nanomachines. Such nanonetworks can represent a new type of communication network that can also be connected to the Internet, enabling fine granular sensing deep inside the organs and tissues inside the human body. This new vision is defined as the Internet of Bio-Nano Things (IoBNT). The focus of this thesis is on developing artificial molecular communication systems for cellular tissues inside the human body. A model and analysis of a Ca2+-signalling-based molecular communication system for embedded nanomachines is proposed. A mathematical framework was developed for 3D tissues of different types of cells that communicate using Ca2+-signalling, where this framework integrates the gap junction behaviour as well as the physiological properties that can affect the communication behaviour. The framework analyses the end-to-end capacity, molecular delay, as well as molecular gain for the different types of tissues. Since cellular tissues are flexible body, the communication process is also modelled considering deformation and structural changes. The thesis also presents communication protocols from wireless communication networks applied to the Ca2+- signalling-based molecular communication system. This includes development of protocols, where channel impairments such as noise and poor information capacity were overcome using communication-by-silence theory in order to improve the end-to-end data rate for "On-Off Keying" modulation. The thesis also focuses on applications of the Ca2+-signalling-based molecular communication system. Firstly, a channel state detection/inference technique that provides information about the current cellular tissue conditions was designed, termed Molecular Nanonetwork Inference Process. The inference process utilizes a simple machine learning algorithm to learn and infer various metrics including the types of deformation, estimated locations of the nanomachines, as well as the concentration of Ca2+ ions used by the transmitters. The second application is based on modelling the tripartite synapse, and focuses particularly on astrocyte cells using Ca2+-signalling to communicate and provide upkeep to the neuronal networks. A feed-forward feedback control technique has been proposed to control synaptic quality in the tripartite synapses molecular communication channel, and this includes regulating the quantity of Ca2+ concentration within the cytosol in order to prevent any dangerous levels that can lead to diseases. At the same time, the feed-forward feedback control model is also used for molecular communication systems in order to prevent excessive noise within the channel, while maintaining decent data rate performance. Creating artificial communication systems that are embedded into the tissue, can lead to new forms of smart tissues that play a major role for future IoBNT vision.
|Unpublished - 2016
- Molecular Communication Systems, Nanomedicine Development