Enabling environment friendly biological cybernetics for biotechnology: from biocomputing to biological AI.

We provide carbon neutral, batteryless and beyond-silicon communications and computing technologies applied to bioengineering, precise medicine, and pharmacology. We use artificial intelligence to design, control and manage technology able towards total coexistence of the syntetic and the natural.

Funding History

  • PI, UKRI BBSRC IAA Engagement Award – Optimisation of exosome-based therapies from 3D BioPrinted stem cell structures. (2023-2024)

  • PI, InnovateUK Knowledge Transfer Partnership, 3D Bioprinting technology for new market solutions in the UK. Participants: University of Essex and iMakr Group. (2022-2024)

  • PI, Marie Skłodowska-Curie Individual Fellowship (EU-H2020-MSCA-IF), STOICISM - Stochastic Communication Inside Cortical Microcolumns. (2019-2022)

  • PI, WIT President PhD Funding, Internet of Nano Things for the Next Generation Theranostics of Brain Glioblastomas. (2019-2023)

  • Co-I, EU-H2020-FET. GLADIATOR: Next-generation theranostics of brain pathologies with autonomous externally controllable nanonetworks: a trans-disciplinary approach with bio-nanodevice interfaces. (2018-2022)

  • PI, Enterprise Ireland Commercialisation Fund, CDaaS – Clinical Data as a Service. (2018-2019)

  • PI, Irish Research Council, Government of Ireland Postdoc Fellowship, Application of Control Theory in Molecular Communication for the Treatment of Alzheimer’s Disease (2016-2018)

  • AI in biology and medicine: Accelerating biological systems modelling and interfacing

    Molecular propagation, interaction, and information encoding are intrinsic to the development, function, and evolution of biological and medical systems and occur in a variety of diverse ways. We use AI to enhance our ability to acquire knowledge of these systems, thereby overcoming the challenges and limitations of experimental biology. In addition, we intend to improve disease detection and treatment by training AI models with limited data that informs biologists and medical professionals. We successfully develop digital duplicates for neurons, astrocytes, smooth muscle cells, epithelial cells, and bacteria, which are 3D+T digital reconstructions of tissues and organs. We work closely with experimental in-vitro data in our in-silico models to develop validated digital twin solutions. Our research focuses on a number of critical areas, including genetic information processing, gene network discovery, molecular biophysical modelling, experimental microscopic imaging analysis, and dynamical biomarker discovery. We intend to stretch the limits of AI in biology and medicine, contributing to a future in which technology and healthcare converge to provide better, more accessible, and individualised medical solutions for individuals around the world.

    Biocomputing using living systems: reducing energy computing costs

    The manipulation, or control, of tissues communication 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.

    Wireless Communications for Biomedical Distributed Interfaces

    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.