In a world increasingly shaped by artificial intelligence, a quieter but equally transformative revolution is taking root – one that doesn’t just live in silicon but breathes, grows, and evolves. Engineering biology, the fusion of biology and engineering principles, is emerging as the next great frontier of innovation. And according to our experts, it will be the key to solving some of humanity’s most urgent challenges – from climate change to food security, healthcare and beyond.
Richard Traherne, Head of Next Frontiers, Capgemini Invent, and CC’s own Head of Biotech Frances Metcalfe, believe biology – when treated as an engineering discipline – could redefine the future of industry, sustainability, and even life itself.
Richard Traherne frames the conversation in the context of a planet under pressure: “Today, we face major global imperatives. But frankly, our current techniques are losing the race. What if there were other ways of doing things? What if we could engineer organisms to capture CO₂, or replace petrochemical products with biologically derived alternatives?”
One of the most striking examples comes from the textile industry. “It’s little known that textiles account for about 10% of our global carbon footprint. That’s more than aviation and shipping combined.”
The solution? Engineering yeast and bacteria to produce new materials. Adidas, for instance, has already created a sports shoe using a silk-like protein called biosphere. “It’s a fibre that’s biologically produced,” he says. “It’s not science fiction – it’s happening now.”
Engineering biology in agriculture
The same principles apply to agriculture, which accounts for 10% of greenhouse gas emissions and 70% of global water usage. “What if we could engineer crops to grow in areas they couldn’t before, using fewer chemicals and less water?
“This isn’t about genetically modified organisms in the traditional sense. This is not GM. That was a blunt tool. This is about deterministic, precise engineering approaches – just like we use for today’s technologies around us – to design new biological systems.”
Healthcare, too, stands to benefit. “What if we had therapies that acted on personal genetic profiles or particular mutations? What if we could unlock treatments that currently don’t exist? The pandemic presented an initial glimpse of what’s possible. mRNA vaccines were the poster child of these techniques, creating societally preserving drugs in double-quick time. There are now just under 300 similar types of vaccines in development globally.
“But the real opportunity lies in reducing the inefficiencies of modern healthcare. Depending on where you look, between 20% and 40% of global healthcare costs are due to ineffective therapies. We’ve all been there – you try one treatment, it doesn’t work, you try another. Engineering biology can help collapse those costs by making care more targeted and effective.”
AI critical in engineering biology
AI is critical to making this possible and has become a fundamental cornerstone of engineering biology. “We’ve been able to read DNA for some time,” explains Frances Metcalfe. “But with more combinations of DNA than atoms in the Universe, AI isn’t a luxury, its essential if we’re to navigate this vast design space.”
Frances describes DNA as the language of life and AI as the tool that allows us to interpret that language. “We can now reprogram biology in the same way we improve human language in a document with ChatGPT. We write some text, and the AI suggests edits we can make to get the improvements we want. We can now do the same with biological code.”
This approach is already yielding results here at CC. One of our projects used a patent-pending protein large language model (pLLM) to improve green fluorescent protein. “We were able to discover a better version of the protein with 99% fewer data points. And it was seven times brighter than any previously published version,” Frances reveals.
This matters because proteins are everywhere – from the food we eat to the materials we wear and the medicines we take. “Antibodies are proteins. Some sustainable materials are made from proteins. The applications are endless.”
A striking example of engineering biology in action is the development of enzymes that can digest plastic. “We worked on a natural enzyme called Cutinase that can break down PET plastic,” Frances says. “But the natural version isn’t commercially viable for a number of reasons, one being it’s not thermally stable enough.
“Using our pLLM, the team created a more robust version of the enzyme. We did it in one iteration, and because we used AI, we explored a much wider range of possibilities than traditional human design would allow.”
New kind of biotech lab
This kind of work is made possible by lab in the loop – a closed cycle of design, build, test, and learn. It’s the approach engineers have used for decades, and CC is now applying it to biology. The labs themselves are changing too. They may look like traditional biotech labs on the surface but underneath, they’re powered by generative and agentic AI, automation and integrated digital systems.
Both Frances and Richard emphasise that this isn’t just about science – it’s about building a new economy. “All of this feeds into the bioeconomy,” says Richard. “It’s a new industrial paradigm where the power of nature is harnessed to engineer new, more sustainable, goods, services, and solutions.”
Capgemini, through CC, has been investing in this area for some time – building multidisciplinary teams that combine biology, data science and engineering. The engineering biology team works with global partners like NVIDIA and Microsoft and is also the World Economic Forum’s partner driving its Bioeconomy Initiative, helping to shape global conversations around the future of biological innovation.
For Frances Metcalfe, it is the convergence of disciplines that makes this moment so powerful. “We’re integrating everything – biology, data science, automation, and AI – into a single workflow. That means we’re not just doing biology differently; we’re doing it faster, more predictably, and more cost-effectively.
“We’re thinking about accessibility and how scientists interact with these tools. It’s not just about the data – it’s about the user experience, the interface, the data foundations and the organisational changes needed to support this new way of working.”
As with any transformative technology – steam , semiconductors, smartphones – engineering biology has the potential for misuse, and guardrails are clearly important. This includes not just standards, policy and regulation, but also public understanding. According to Richard Traherne, the term ‘engineering biology’ isn’t very accessible, so better storytelling is needed to help people understand what this is and why it matters.
Frog, Capgemini’s design and innovation consultancy, is helping with that: “They’re employing policy lab and storytelling initiatives to develop a narrative that develops accessibility and trust. Because if we don’t tell the story well, we risk losing public confidence.”
The message, however, is clear: engineering biology is not a distant dream – it’s here, it’s real and it’s ready to scale. Richard and Frances see it as a ChatGPT moment for biology. With the forces of AI, computational power, ecosystem support and sustainability imperatives all aligning, the time is now. For those who embrace it, the rewards could be transformative. The companies that harness AI, automation, biology and design will be the ones that will lead and ultimately win.
