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Enzyme engineering startup Imperagen raises £5M

Enzyme engineering startup Imperagen raises £5M

Woodenscale AI
Woodenscale AI
5 min read

Imperagen is an enzyme engineering startup that uses quantum simulation, AI, and robotics to design better enzymes faster. The Manchester company raised a £5 million seed round on Thursday. PXN Ventures led the deal, while IQ Capital and Northern Gritstone also participated. The pitch is simple: enzyme engineering is still too slow and too dependent on lab-heavy trial and error. Imperagen was founded in 2021 by Dr. Andrew Currin, Dr. Tim Eyes, and Dr. Andy Almond as a spinout from the University of Manchester’s Manchester Institute of Biotechnology.

What does Imperagen’s enzyme engineering platform do?

Imperagen’s product is a closed-loop enzyme engineering system. A customer starts with an enzyme problem — maybe they need a catalyst that works faster, survives harsher process conditions, or performs a very specific chemistry. Imperagen models that reaction at quantum-physics level, uses AI to prioritize promising variants, then tests those candidates in an automated lab before feeding the results back into the model. It’s a design-build-test-learn workflow, with a much heavier emphasis on mechanistic simulation than most AI protein tools.

That matters because lots of protein-design platforms still begin with sequence guessing and then rely on big rounds of wet-lab screening to see what sticks. Imperagen is trying to cut out a lot of that blind searching. Its system explores millions of mutation combinations in silico, then narrows the field before the physical work starts. It still needs experimentation. But each cycle should be more informed and less wasteful.

The company calls the underlying stack Digital Enzyme Evolution. On the lab side, it uses high-capacity robotics that can test up to a few thousand variants in a run. That’s where the feedback loop becomes useful instead of theoretical. Data from those experiments retrains problem-specific AI models, so the system gets better as it works through a customer’s exact chemistry instead of relying only on broad protein data.

It isn’t framed as a one-enzyme niche tool. Imperagen has already evaluated compatibility across multiple enzyme classes used in pharma and industrial biocatalysis, including oxidases, reductases, transaminases, and glucosidases. For customers, the promise is less “here’s an AI model” and more “here’s a faster way to get to a production-ready biocatalyst.” That’s a stronger commercial pitch if the science holds up outside the lab.

Who founded the enzyme engineering startup Imperagen?

Founded in Manchester to fix a stubborn chemistry problem

Imperagen came out of the Manchester Institute of Biotechnology, where the founding team had been attacking enzyme design from different angles. One stream was computational — advanced models that could screen huge mutation sets. The other was experimental — better ways to build and test enzyme variants in the lab. The founding idea was that combining those two approaches would beat the old method of repeated random mutation and screening.

That origin story fits the product. A lot of biotech startups bolt AI onto an existing workflow and call it a day. Imperagen seems to have been built around the workflow from day 1.

Why this founding team fits the job

Dr. Andy Almond, now CTO and co-founder, brings the clearest startup track record. He’s a biophysicist and previously co-founded C4X Discovery, which went public in 2014. That matters because Imperagen isn’t just a research project anymore. It needs somebody who understands how to turn hard science into a company people will actually buy from.

Dr. Andrew Currin, the company’s CSO and co-founder, is the deep technical anchor. He’s an expert in directed evolution and synthetic biology. He’s also credited with the patented gene-assembly technologies behind Imperagen’s automated platform. Tim Eyes, a co-founder who now serves as director of programs, came up through protein engineering, started his career in therapeutic biotech, and held an Enterprise Fellowship at the University of Manchester. The mix is tight. Biophysics, enzyme science, and protein engineering all map directly to a company trying to industrialize biocatalysis.

Fundraising, early signals, and where Imperagen sits against rivals

PXN Ventures led the new £5 million seed round, with IQ Capital and Northern Gritstone participating, and it takes Imperagen’s total funding to £8.5 million. On the same day, the company said Guy Levy-Yurista will become CEO, while the founding scientists stay in the business. Before this round, Imperagen had already picked up a £350,000 UKRI engineering biology award in March 2024 for work on its Digital Enzyme Evolution platform. That gave the science some external validation before the new capital arrived.

Competition is real, and it’s not all the same. Cradle is building a SaaS-style protein design platform and raised $73 million in late 2024 to expand its wet lab and software reach. Biomatter has pitched a more de novo, generative approach to enzyme design and raised a €6.5 million seed round to push that model further. Absci sits in a bigger, more therapeutics-heavy category, combining AI and synthetic biology with a large wet-lab data engine for protein drug creation. Imperagen’s angle is narrower and more practical: it’s focused on industrial biocatalysis and enzyme engineering problems where mechanistic chemistry, robotics, and real manufacturing constraints matter more than flashy sequence generation alone. The legacy alternative isn’t another startup. It’s directed evolution by hand, contract labs, and long development cycles.

Why does this enzyme engineering startup funding matter?

This round matters because it looks like a shift from spinout science to company-building. Imperagen said the new money will go into hiring more AI specialists, expanding R&D, building out experimental lab capacity, and creating a go-to-market function over the next 2 years. This isn’t a keep-the-lights-on raise. It’s a build-the-machine raise.

The CEO hire is part of that. Levy-Yurista comes in with a background across AI, life sciences, and enterprise technology, and his brief isn’t subtle: build a vertical AI infrastructure for biocatalysis, sharpen commercial models, and add industrial partnerships. Investors aren’t just betting on better models. They’re betting on a company that can package those models into a repeatable product.

His framing is also more grounded than a lot of biotech AI talk. He’s argued that many AI-led enzyme tools can beat trial-and-error in theory but still fail when pushed to industrial scale in practice. So the pitch here isn’t magic. It’s to make enzyme development “faster, more reliable, and more commercially accessible,” helping companies bring bio-based products to market without the usual delay and uncertainty.

How big is the market for AI enzyme engineering?

The commercial backdrop is big enough to get investor attention. Grand View Research estimated the global engineered enzymes market at $2.78 billion in 2024 and projects it to reach $7.32 billion by 2033, which implies an 11.6% CAGR. In the U.S. alone, the broader enzymes market was estimated at $3.8 billion in 2023, with projected annual growth of 6.7% through 2030.

The demand drivers are pretty clear. Pharma needs more selective catalysts for drug manufacturing. Food and agriculture keep looking for cleaner processing tools. Industrial chemistry is under pressure to lower energy use and swap out harsher reaction conditions where it can. Enzymes sit right in the middle of that shift, which is why so many techbio companies are piling into protein design right now. The hard part isn’t explaining why the market exists. It’s proving a platform can deliver enzymes that survive real production environments, not just elegant demos.

Can Imperagen turn enzyme engineering into software?

That’s the bet.

Imperagen has the ingredients investors usually want in a deep-tech biotech company: scientific depth, a founder team with domain credibility, a new CEO brought in for commercial scale, and a product story that goes beyond generic “AI for biology” claims. But this category is unforgiving. If the company can show that its closed-loop platform consistently produces enzymes that work on industrial timelines and economics, this enzyme engineering startup could become one of the more interesting biocatalysis companies to watch over the next 24 months.

Read how Stilta raised a $10.5M seed led by Andreessen Horowitz to automate the repetitive research and analysis behind patent litigation with AI agents that generate claim charts, prior art searches, and case-ready legal reports.

FAQ

What funding did Imperagen raise? Imperagen raised a £5 million seed round announced on Thursday. PXN Ventures led the deal, and IQ Capital plus Northern Gritstone joined in. The raise brings the company’s total funding to £8.5 million and is meant to support hiring, R&D, lab expansion, and commercial buildout.

How does Imperagen’s platform work? It works as a closed-loop enzyme engineering system that combines quantum-level simulation, AI ranking, and robotic lab testing. Instead of mutating enzymes mostly by trial and error, Imperagen models likely outcomes on a computer first, tests the best candidates in the lab, and feeds that experimental data back into the model for the next round.

Who founded Imperagen? Imperagen was founded in 2021 by Dr. Andrew Currin, Dr. Tim Eyes, and Dr. Andy Almond, all scientists tied to the Manchester Institute of Biotechnology. Their backgrounds span directed evolution, protein engineering, synthetic biology, and biotech company creation, which is why the founding team looks credible for this very specific problem.

What market is Imperagen in? Imperagen sits in enzyme engineering and industrial biocatalysis, with overlap into techbio and AI-driven protein design. Its target customers are companies using enzymes in pharmaceuticals, food, biofuels, agriculture, and other manufacturing workflows where better catalysts can cut time, cost, and process complexity.

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