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Adaptyv Bio Secures €34.35M Series A to Scale AI-Driven Protein Design Lab

Adaptyv Bio Secures €34.35M Series A to Scale AI-Driven Protein Design Lab

The biotech sector is witnessing a significant acceleration in drug discovery, as Adaptyv Bio, a Swiss startup, has raised a substantial Series A round to expand its automated lab for AI-driven protein design. This funding aims to break the bottleneck in validating AI-generated protein candidates, which traditionally slows down the development of new medicines and biomaterials.

THE STORY

The burgeoning field of AI-driven drug discovery is often hampered by the slow and labor-intensive process of validating computationally designed proteins in physical wet labs. Lausanne-based Adaptyv Bio is directly addressing this challenge, securing €34.35 million ($40 million) in Series A funding to scale its automated, AI-native laboratory platform. This investment, led by Highland Europe, with continued participation from existing investors like Ace Ventures, ByFounders, and Y Combinator, will allow the company to significantly expand its capacity and tackle more complex biological problems.

Adaptyv Bio's platform integrates advanced robotics, microfluidics, and synthetic biology to transform digital protein sequences into real-world experimental data. This automated workflow handles everything from in-house DNA synthesis and protein expression to precise binding measurements, drastically reducing the turnaround time for experimental results. By providing rapid and reliable validation, Adaptyv Bio enables protein engineers and AI models to receive faster feedback, accelerating the iterative design cycles crucial for developing novel therapeutics and materials.

The startup's approach is particularly critical as generative AI models become increasingly adept at designing thousands of protein candidates in a short period. Traditional labs are ill-equipped to test such volumes, creating a validation gap that Adaptyv Bio aims to close. The company plans to triple its lab capacity by the end of 2026 and open a new lab and office in London, alongside its Lausanne operations, growing its team from 25 to around 60.

This expansion reflects a broader industry trend towards 'agentic biology,' where AI systems can autonomously design, execute, and learn from biological experiments. Adaptyv Bio's long-term vision is to build a 'biological gigafactory' with enough automated experimental capacity for AI to learn from physical reality as quickly as it learns from text, effectively removing lab throughput as a constraint on biological progress. This move positions Adaptyv Bio as a key infrastructure provider in the evolving landscape of AI-powered life sciences.

INTELLIGENCE BRIEF

WHY IT MATTERS

This funding round for Adaptyv Bio highlights the growing investment in technologies that bridge the gap between AI's computational power and the physical world of biological experimentation. By automating wet lab processes, the company is not only accelerating drug discovery but also enabling AI models to learn more effectively from real-world biological data, which is crucial for advancing fields like synthetic biology and personalized medicine. This shift could dramatically reduce the time and cost associated with bringing new biological innovations to market.

WHO IS INVOLVED

Julian Englert (CEO and Co-founder of Adaptyv Bio), Daniel Nakhaee-Zadeh Gutierrez (Co-founder of Adaptyv Bio), Highland Europe (Lead Investor), Ace Ventures, ByFounders, Y Combinator (Investors).

MARKET IMPACT

The success of Adaptyv Bio's model could set a new standard for how biological research and development are conducted, pushing the entire biotech and pharmaceutical industry towards more automated, data-driven approaches. It signifies a move towards 'biological gigafactories' where AI can continuously iterate and learn from experiments, potentially democratizing access to advanced protein engineering capabilities and accelerating the development of novel therapies and biomaterials globally.

This story was drafted with AI assistance and reviewed by TurkSpark editors before publication. Facts, figures, and names may be inaccurate — verify important details independently.

BiotechAIDrug DiscoveryRobotics