AI is already changing how we work with computers, but it might also change how we interact with the human body.
Demis Hassabis, CEO and co-founder of Google DeepMind, says AI can play a big part in reshaping biology. He described a world where AI could simulate complex biological systems, even down to the cellular level. Hassabis believes that AI can become the descriptive language of biology, just as mathematics perfectly describes physics. This powerful analogy suggests a future where biological complexity can be understood and manipulated with unprecedented precision.
“I feel we’re entering a new era now of what I call digital biology,” Hassabis said. “I think of biology, at its most fundamental level, as an information processing system that’s trying to resist entropy around it. And I think that’s basically what life is, of course. It’s a phenomenally complex and emergent information processing system.”
He continued, “And I think that’s where AI comes in. Just like maths – and the maths that I learned in this room was the perfect description language for physics – I think that AI is potentially the perfect description language for biology. It’s perfect for dealing with the complexities of the emergent behaviors and interactions that you get in a dynamic system like biology.”
“And so we think of this as a kind of doing science at digital speed, so trying to bring the best of what we do in the technology area to the natural sciences,” Hassabis explained. “And my dream one day is to be able to create maybe a kind of virtual cell, a computational cell perhaps of something very simple like a yeast cell, and that you can actually run experiments *in silico* on it. And the predictions that you get out of the virtual cell will actually inform your real-world experiments in the lab, and you can reduce down a lot of the search that’s done in the wet lab and actually more use the wet lab for validation steps rather than the very expensive and slow search process.”
Hassabis might be leading an AI lab, but biology is very much within his wheelhouse. DeepMind had solved protein folding through its AlphaFold program in 2018, and had discovered the structures of all 200 million known proteins. Hassabis had been awarded the 2024 Nobel Prize in Chemistry for his contributions.
Hassabis’s vision about AI being the language of biology could have profound implications. If researchers are able to model the effects of a new drug on a virtual cell, it could accelerate drug discovery and personalized medicine. The development of virtual cells could revolutionize our understanding of diseases, allowing scientists to simulate disease progression and test potential treatments in a risk-free environment. This “digital speed” science could drastically reduce the time and cost associated with traditional biological research.
Furthermore, the ability to create virtual cells could open doors to synthetic biology, enabling the design and construction of new biological systems with specific functionalities. This could lead to advancements in areas like biomanufacturing, bioremediation, and even the creation of artificial life forms. While the realization of a fully functional virtual cell remains a significant scientific challenge, Hassabis’s vision, combined with the rapid advancements in AI, suggests that this ambitious goal may be within reach sooner than we think.