A Biotech Leader’s Path Across Continents
An interview by Stefan Janssens
Dr Elena Brevnova had only recently arrived in London when we met at a film meetup. She was doing what people do in new cities, trying new experiences, even if that meant watching horror films with strangers. Horror is not really her genre, she admitted. And yet something in Sam Raimi’s Send Help connected with her, the part where a woman navigates a system that rewards louder men. Elena did not choose the same strategy as the protagonist. She chose something steadier. Build. Excel. Stay.
She also remarked on the cultural differences from the US. In the US, popcorn at the cinema feels compulsory. In London, it seems optional. So does fish in a poke bowl, she added, during the post film meetup at a plush hotel bar that unexpectedly served it vegetarian.
A few weeks later we talked about Russian films, about cities, about science, about swimming ponds, stubborn optimism required to keep going.
Dr Elena Brevnova is a protein engineering and synthetic biology expert. She is a Co-Founder of Aise Bio, where she leads the development of AI‑powered protein expression optimization tools that accelerate discovery and design in biotech. She also serves as Head of Molecular Biology at Epoch Biodesign, leading strain engineering and enzyme production for AI-driven biocatalysis, and previously held senior organism engineering roles at Boston-based Ginkgo Bioworks.
Q&A with Elena Brevnova
When we first met, you mentioned a Russian film you think everyone should watch. Not the usual classics, but something more lived in.
Elena: Yes. The Irony of Fate, or Enjoy Your Bath! It’s one of my absolute favourites. The title comes from a Russian expression you say to someone heading to the sauna. It doesn’t translate properly. It’s a romantic comedy, but also satirical. It was directed by Eldar Ryazanov, who was famous for subtly criticising the system while technically making films that were supposed to celebrate it.
Everyone knows the quotes. It plays every New Year’s Eve. You can watch it again and again and still find something new. It’s comforting, funny and nostalgic.
“You can watch it over and over and still find something new.”
You’ve lived in Moscow, Boston, and now London. What did arriving here feel like?
Elena: London is amazing. I’m still not sure if I love the UK as a whole, because I don’t know it well yet, but I absolutely love London. It feels like its own little universe.
It’s incredibly diverse. Green. Full of parks. Compared to New York, it’s not as tall, so it feels more open. The Tube could really use air conditioning. That would help. But structurally and culturally, it kind of has everything.
New York has incredible people. But I never loved the city itself. Moscow is architecturally beautiful. But culturally it is much less diverse . London feels perfectly balanced.
“London feels like its own little universe.”
And at work? Did the culture shift as much as the geography?
Elena: Yes, actually. What struck me immediately was how much less competitive it feels here. People are just as smart and talented. But they’re not constantly trying to outdo each other to get promoted.
I have someone on my team who delivered a huge breakthrough. Amazing data. And then he took three weeks off. Completely disconnected. In the US, that would be almost unthinkable. Here, he delegated and left. It creates a warmer atmosphere. I think people are happier. And maybe more productive because of it.
Many in the US prefer coffee over tea, but I saw an office photo of you holding a comically gigantic bag of Yorkshire tea.
Elena: I’m definitely a tea person. In the US, it’s coffee everywhere. Tea almost feels discriminated against. Once in San Francisco, I ordered hot tea and they had to go to a grocery store to get it for me.
“I’m definitely a tea person.”
Here, we have gigantic bags of tea in the office. I sent the photo to my American friends because it would look exotic and funny to them.
Let’s talk about your journey into biotech. Has anything changed for you since your last interview in 2022 with the Equality Pursuit, especially regarding women in science?
Elena: It’s getting better. But it’s not 100 percent. And it’s in all sectors. Not specific to science or bio tech.
For a long time in the US, there were more CEOs named John than all female CEOs combined. I wouldn’t be surprised if that’s still true.
With my side company, we realised we had a much better chance of raising money if a man presented as CEO. Investors, mostly older white men, trust other men with their money. “Deliver great results. And make sure you get recognition for your work.”
At the same time, I do see progress. I recently interviewed a female executive in a very technical engineering role. That would have been rare before. Engineering has always been male dominated. Now women are making it to the top.
Now going back to 2020. During COVID, biotech suddenly became central to everyone’s life. What was that period like for you?
Elena: Honestly, it was exciting. I know that sounds strange and I am a bit embarrassed to say it . I was at Ginkgo, and they shut down all projects unrelated to COVID. I couldn’t get a leadership position at first on Covid project, so I volunteered to go back to the bench. I was already a manager. But I just wanted to help. I couldn’t stay home.
I realised how much I missed doing experiments.
Eventually I got a small team and we developed pooled COVID tests for schools. We worked with live COVID samples before vaccines were available. It was scary. But it felt like we were saving the world. It’s probably the most direct impact I’ve ever felt from my work.
“It felt like we were saving the world.”
Did any of that work become a commercial product?
Elena: Yes, the pooled testing became Ginkgo Concentric, used in schools and maybe airports. The idea was to combine samples from a group into one tube, and the test was sensitive enough to detect even one positive out of fifty. If the group tested negative, everyone was fine; if positive, you’d test them individually.
Apart from your innovations with COVID testing, you also hold patents related to cannabinoid biosynthesis. For people outside biotech, what does that actually mean?
Elena: There are more than 140 cannabinoids in cannabis. We usually only hear about THC and CBD. But many rare cannabinoids have interesting and useful health properties. The problem is they’re present in tiny amounts in the plant. It’s very hard to extract enough.
So we engineered microorganisms. We transferred the plant pathways into them so they could produce these rare molecules at scale. One project led to a Canadian company making gummies with some of our cannabinoids. Nature has all these molecules. We just need better tools to access them.
So, what are you working on at the moment? Because you work for a company and your own startup. Could you summarize what you do for both?
Elena: My main job is with a wonderful, very exciting London startup called Epoch Biodesign. They’re tackling the massive problem of plastic waste. The idea is simple in theory and very hard in practice. We take plastic waste from producers and recycle it, turning it back into new plastic so it doesn’t end up in landfills or incinerators.
What’s really thrilling is how we do it. We use enzymes. And even more exciting, we design those enzymes using AI.
“It genuinely feels like we’re at the forefront of something big.”
The AI helps us create enzymes that can digest plastic polymers. Plastics are long chains of molecules. The enzymes break those long chains into monomers, the building blocks. Then those monomers can be rebuilt into new polymers. So it’s a circular system. We are saving the planet from plastic contamination.
It genuinely feels like we’re at the forefront of something big. You can feel it in the lab. There’s this sense that if we get this right, it changes the equation.
You mentioned large language models earlier. I kind of understood how LLMs work for different applications, different industries. But for some of our readers perhaps their interaction with AI is via language models only like ChatGPT, so they might have a hard time connecting it to how it help you with breaking down plastic. Can you help explain?
Elena: Of course. Large language models are just one type of machine learning model. The principle is that you train them on large datasets and they learn patterns.
In our case, we’re not training on poetry or text. We’re training algorithms on enzyme data. We feed in information about enzyme sequences and properties, about which ones degrade plastic, which ones are stable at certain temperatures, which ones function under industrial conditions.
The algorithm learns patterns in that data. It can then suggest new enzyme sequences that might work better. Faster degradation. More stability. Better performance under real manufacturing conditions.
It’s powerful because we don’t have to test everything blindly in the lab. The AI narrows the search space. It suggests promising candidates. Then we validate experimentally.
It’s not magic. We still do the biology. But it accelerates everything.
“It’s not magic. We still do the biology. But it accelerates everything.”
And your start-up AISE bio uses a similar philosophy?
Elena: Yes, but applied differently. I co-founded AISE Bio, based in Boston. We’re building a universal algorithm trained on protein production data in microorganisms.
Here’s the problem: you might design a fantastic enzyme. Or an antibody. Or a cannabinoid pathway. But if the microorganism can’t produce that protein efficiently, it’s not commercially viable. You can’t scale it.
Our algorithm predicts how to slightly modify the protein sequence so the host organism produces more of it. Better expression. Higher yield. Commercially scalable.
This is crucial. Because so many promising biotech ideas fail at that step. They work beautifully in theory. Then production becomes the bottleneck.
We’re trying to remove that bottleneck.
“Our algorithm predicts how to slightly modify the protein sequence so the host organism produces more of it. Better expression. Higher yield. Commercially scalable.”
Do you have a concrete example of how this works in practice?
Elena: Yes. Right now, we’re helping another company produce antibodies in CHO cells, which are hamster cells commonly used in pharma manufacturing.
Antibodies are medicines for many diseases. Cancer. Autoimmune disorders. Infections. They’re incredibly important.
Our algorithm can slightly tweak the antibody sequence, without changing its therapeutic function, so that the CHO cells produce much more of it. That means lower production costs, better scalability, more access for patients.
For me, that’s where it becomes real. It’s not just abstract AI. It’s something that can reduce the cost of medicine or make recycling plastic feasible at scale.
It’s very rewarding. It’s a lot to juggle. But it’s exciting.
That’s all very promising and exciting indeed! With all of that, how do you switch off? What do you do to unwind?
Elena: I force myself to disconnect. Even four days helps. I recently went to Barcelona and decided no Slack, no email. Only WhatsApp for emergencies. It was very therapeutic.
I loved Gaudí’s architecture. So colourful. Almost fairytale like. And the seafood on the beach. You pick your fish and they cook it right there.
In London, I live near the Highgate ponds so I can swim. In summer, I can swim for hours. I wish the lakes were bigger. But they’re good for now.
In winter, I love skiing. I ski a lot with my daughters in Vermont. I’ve only been to the Alps once, but it was incredible. I’m always looking for company to go again.
If you zoom out, across cities, visas, patents, start-ups, what ties it all together for you?
Elena: Impact. I want my work to matter. During COVID, it was obvious. With plastic recycling, it’s obvious. With rare molecules, it’s about making things accessible.
There will always be constraints. Visas. Bias. Funding structures. You can spend all your time being angry. Or you can figure out how to move forward anyway. I prefer the second option.
“Impact. I want my work to matter. During COVID, it was obvious. With plastic recycling, it’s obvious. With rare molecules, it’s about making things accessible.”
IN CLOSING
Dr Elena Brevnova approaches science the way she approaches cities. Observe carefully. Understand the system. Then redesign what you can.
She has navigated immigration rules, gender bias, and overheated Tube carriages with the same composure she brings to enzymes and code. There is ambition there, certainly. But also humour. And tea. And long swims in cold water.
At that first film meetup, horror was not really her genre. Building is.
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