We combine multi-scale models of wireless and molecular communications with biological cell signalling models in order to provide precise and targeted sensing or treatment of diseases. We use unconventional medical devices that range from metamaterials to synthetic biological devices, and combinations thereof.
Molecular communciations is a recent interdisciplinary research area that integrates concepts from telecommunications and computer networks for the dual goal of 1) designing communication using molecules for synthetically engineered cells or unconventional implantable medical devices and 2) further analyse biological communications for deeper understanding of tissues and organs functioning. We have sucessfully designed communication system models using in-silico and in-vitro models of different types of biological systems including, neurons, astrocytes, smooth muscle cells, epithelial cells as well as bacteria. We work close with experimental in-vitro data in our in-silico models with the vision of developing validated digital twins solutions that one day can be translated to clinical practices. This research is supported by European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 839553.
The manipulation, or control, of tissues enables the possibility of further exploring novel activity patterns that derives new ways of tissue behaviour. Biocomputing can be derived from this vision, where we have proposed that the communication of cells can be optimitized in a way that performs Boolean logic gates. We have used different types of cells, by which we have succesfully achieve the obtention of logic gates functions in astrocytes, neurons and bacteria. We have developed both in-silico and in-vitro models that show such technology can be achieved. We have designed control and optimization models that range from control theory mathematical derivations to machine learning-based optimizations. Our plans for the future include the deep exploratory work that will answer how many logic gates and circuits can be obtained from this approach as well as what biological parameters should be consider to provide full optimised solutions that are safe to be implanted. We will also expand our analysis to derived in-vitro models that show the possible sensing and treatment technology that can emerge from biocomputing systems, where the vision is to provide more efficient and biocompatible solutions than existing biomedical devices.
The large scale and long term implantation of unconventional medical systems depends on the distribution of the devices or externally controlled cells that produce a desired, but yet very precise, sensing or actuation in the body. This is only possible if these systems are communicating to each other as well as to the outside the body. We term this technology as in-vivo networking, which we consider as one of the stepping stones for the developed of the futuristic vision of the Internet of Bio-Nano Things. We have developed networking protocols for ultrasound-based communications between external and implantable devices. We focus on the manipulation of ultrasound signals to perform not only communication but to provide energy to bateryless implantable systems for neural interfaces, which is used as a sensing mechanism of biological neural networks powered by AI. We are now expading to multiple communication channels that can use ultrasound signals as well as optical and RF-mmWave. We are also further validating our models using 3D ex-vivo-based platforms testing how wireless signals can be changed to overcome signal losses and impedance mismatching towards high-bandwidth interfaces.