Cybergenetics, Generative AI and Virtual Cell Models

Cybergenetics is an emerging discipline at the intersection of control engineering and synthetic biology, dedicated to the rational design and real-time control of genetic circuits in living cells. Inspired by Norbert Wiener's foundational vision of cybernetics - which unified control and communication principles across machines and living organisms - cybergenetics applies feedback control theory to biological systems. This field enables engineers to treat DNA as a programmable template, creating robust genetic controllers that achieve precise regulation despite cellular noise, parameter uncertainty, and environmental perturbations. From simple negative feedback loops that confer robustness (analogous to classic electronic amplifiers) to advanced proportional-integral-derivative (PID) controllers implemented at the molecular level, cybergenetics transforms cells into programmable devices capable of sophisticated computation and decision-making.

 

At the University of Edinburgh, this research theme unites cybergenetics with generative artificial intelligence and virtual cell modelling to pioneer the next era of digital biology. By creating hybrid systems that blend real-time biological control with predictive computational tools, we are accelerating the design of living systems for biomanufacturing, environmental sensing, and precision medicine.

 

The cSynBioSys Group, led by Professor Filippo Menolascina, has played a pivotal role in establishing cybergenetics as a field. Recognised as one of its pioneers, Prof. Menolascina's seminal contributions include the first demonstrations of in vivo real-time computer control of protein expression from both endogenous and synthetic gene networks, as well as the development of cybergenetic systems for behaviour control in poopulations of bacteria. Prof Menolascina's group introduced groundbreaking innovations such as cybergenetic twins - hybrid digital-biological replicas of bioprocesses that enable real-time, genome-wide monitoring of cellular states in microfluidic environments. These systems empower intelligent algorithms to detect deviations and intervene dynamically, dramatically improving efficiency and resilience in biomanufacturing applications ranging from mRNA vaccine production to cultivated meat.

 

Building on this foundation, Dr Luca Bandiera is extending the cybergenetics paradigm toward a new generation of living therapeutics. His work focuses on engineering precise cybergenetic controllers to identify treatments to human diseases like MASLD. By integrating control-based  methods and multi-input optogenetic systems, Dr Bandiera's research is creating new approaches to combination therapy optimisation - opening transformative possibilities for personalised medicine.

 

Complementing these experimental advances, the theme harnesses generative AI to automate the design of complex genetic circuits, evaluating billions of configurations to produce robust, cost-effective solutions that match user-specified behaviours. Coupled with virtual cell models, these AI-driven approaches enable rapid in silico prototyping and optimisation, dramatically shortening the traditional design-build-test-learn cycle and bridging the gap between computational prediction and biological reality.

 

Together, these integrated capabilities position the University of Edinburgh at the forefront of programmable biology, where living cells become reliable, controllable platforms for addressing humanity's greatest challenges - from sustainable biomanufacturing to next-generation therapeutics.