Finnish protein engineering company Avenue Biosciences has raised $5.7 million in a Seed extension funding round co-led by Balnord and Tesi, with support from existing investors Voima Ventures, Inventure, University of Helsinki, and Dimerent.
The funding aims to help scale its high-throughput protein engineering technology that accelerates the discovery of protein-based therapies and tools for the biotechnology industry. The financing brings Avenue Biosciences’ total funding raised to date since 2024 to $8.7 million.
I spoke to Katja Rosti, co-founder and COO, to learn more.
Avenue Biosciences is dedicated to accelerating the discovery and development of protein biologics – drugs made using living cells, designed to treat disease by targeting specific pathways in the body in a more complex manner than traditional drugs, but whose complexity also makes them difficult to manufacture at scale.
Why modern biologics are so powerful — and so hard to make
Modern biologics have been available for several decades; typical examples include human insulin and antibodies for treating breast cancer and rheumatoid arthritis.
However, much life-saving therapy goes unrealised because of production barriers, particularly the cell’s limited ability to correctly fold and secrete complex proteins.
In response, Avenue Biosciences has developed what it describes as the first platform to measure and modulate the secretory pathway at scale. It combines organic biology and machine learning to boost protein production through a proprietary approach grounded in years of scientific research at the University of Helsinki, Finland.
According to Rosti, several factors have held the field back from making this possible earlier.
She contends that although signal peptides — short amino-acid sequences that act as address labels, telling the cell where to send a newly made protein before it is removed from the mature molecule — were identified as early as the 1980s, this knowledge remained largely academic for decades.
“These signal peptides operate within the secretory pathway: the cell’s internal machinery that transports proteins from their site of synthesis to their final destination, most often outside the cell, to the cell membrane, or to other organelles.
For therapeutic proteins, this pathway is critical, because this step often determines whether a biologic can be manufactured at all.”
When the science was largely there, but lacked a platform
For a long time, however, the biological understanding of this system was incomplete, and the tools needed to explore it systematically and at an industrial scale simply did not exist. Beyond technical constraints, Rosti also cites an organisational and cultural dimension.
“Biotech development tends to rely on established workflows,” she shared.
“Traditionally, companies have worked with a small set of well-characterised “safe” signal peptides, optimising expression through slow, sequential trial and error.
The idea of screening thousands of signal peptide variants in parallel, early in development, was neither technically feasible nor part of standard practice.”
In other words, until now, as with many breakthroughs, the pieces of the puzzle were already there — the biology, the industrial relevance, and the unmet need, ”but no one had yet assembled them into a scalable, integrated platform.
While biology gets smart, the secretory pathway is still a black box.
But even with today’s tools, the secretory pathway is still not fully understood, which, according to Rosti, makes it such a powerful frontier for innovation:
“As biological insight deepens, new parameters can be mapped and exploited, allowing the technology to evolve in step with scientific discovery.”
Novel protein-based biologics under development, for example, in cancer, rare diseases, or immunology, are becoming increasingly targeted and effective, performing several functions with a single therapeutic component: bringing immune cells to the right place, activating them, and recognising disease cells more specifically.
“However, this adds complexity to the protein structure, adding manufacturing cost, or in the worst case, preventing the development completely”, shared Rosti.
“Ultimately, the signal peptides are removed from the mature protein, keeping the target essentially the same as the original, making this approach highly useful also in manufacturing biosimilars, the lower-priced versions of existing therapies.”
How Avenue Biosciences is cutting years from protein development timelines
To scale without slowing down or driving up costs, Avenue Biosciences has built its platform around massively parallel testing. Instead of trying to improve protein secretion one signal peptide at a time, the company screens thousands of variants in a single experiment, dramatically shortening development timelines.
“When a customer gives us a target sequence, we combine it with a library of about 5,000 to 6,000 different signal peptides,” says Rosti.
“These peptides act as the molecular ‘addresses’ that guide the protein out of the cell and into the culture medium, which is essential for large-scale manufacturing.”
This high-throughput approach replaces what is still the industry norm: sequential trial-and-error.
“Today, most teams test one signal peptide, tweak the conditions, then try another. It’s a slow, inefficient process,” Rosti explains.
“By screening thousands in parallel, we can identify the best-performing variants in a single experiment, which is where the real time and cost savings come from.”
The economic impact is particularly significant for late-stage development, where expression problems can quietly derail years of R&D investment.
“There is a lot of hidden cost in projects that fail simply because the protein cannot be produced at sufficient yield,” she says.
“In some cases, we can step in late and actually rescue a programme by improving secretion without changing the therapeutic target itself. We’re effectively adding a booster to the molecule.”
Where wet-lab reality meets machine learning
While there’s plenty of noise around AI in biotech right now, Rosti holds close to her roots as a protein scientist, considering wet-lab biology as fundamental.
“AI-designed proteins may look promising in silico, but that doesn’t guarantee they can be produced in cells,” she shared.
"We use experimental data from large-scale screening to train machine-learning models.
This helps us understand patterns, refine libraries, and improve prediction. At the same time, computational insights can guide future experiments. It’s a two-way relationship.
A company may design a protein using AI and bring the sequence to us for real-world validation. But biology always has the final say.”
From research to business Crucially, Avenue Biosciences has had the home advantage of being the company’s first customer, validating its own platform, meaning the technology was already well validated during the research-to-business phase.
“We came out of stealth at the end of 2024 and quickly gained customer traction,” explained Rosti.
“We generated revenue in our first year, which is encouraging. Today’s customers are established CDMOs and pharmaceutical companies," because, according to Rosti,
“They already understand the limitations of current secretion strategies and see the need for better solutions.Protein expression challenges vary widely, so collaboration is essential.“
Investors say Avenue is addressing one of the most fundamental and undersolved bottlenecks in biologics manufacturing,
“Avenue’s technology taps into some of the largest opportunities in biotech right now: it significantly lowers the costs of biologics and transforms therapeutic protein manufacturing with the use of AI. Their combination of wet lab and machine learning enables the development of high-quality prediction tools for therapeutic developers, targeting the biggest bottlenecks in the industry. The team has shown incredible execution, with really strong industry names as their clients”, comments Gabriele Poteliunaite, Investor at Balnord.
“Many life-altering therapeutic innovations remain out of reach for most of the global population. We see significant growth opportunities for Avenue’s technology, which is deeply rooted in Finnish scientific discovery, and has the potential to become a gold standard in its field”, comments Investment Director Miia Kaye from Tesi.
The funding will be used primarily to invest in people and scientific capability. According to Rosti
“We are hiring wet-lab scientists to work on core technology and customer projects. Knowledge building is our priority. Commercial expansion will follow, but the foundation is biological expertise.”
Lead image: Avenue Biosciences COO Katja Rosti and CEO TeroPekka Alastalo.Photo: uncredited.
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