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Sortera Bio pioneers biologics discovery through its proprietary Deep Screening technology, which generates extensive sequence-function datasets. This approach leverages artificial intelligence models to achieve significant speed and precision in the identification of therapeutic candidates, fundamentally transforming the initial stages of drug development. The platform offers enhanced control over the discovery process, aiming to streamline the traditionally lengthy timeline for novel biologics.
The company was co-founded in 2023 by Dr. Ben Porebski and Dr. Philipp Holliger, emerging as a spin-out from the MRC Laboratory of Molecular Biology. Both founders are distinguished experts in the fields of protein engineering and synthetic biology, bringing a deep understanding of complex biological systems to their innovative venture. Their collective insight into the potential of combining advanced screening with AI laid the groundwork for Sortera Bio's methodology.
Sortera Bio’s platform is designed for pharmaceutical partners seeking to accelerate their biologic pipelines. The company's vision centers on redefining early biologics discovery and engineering by providing a sophisticated tool for drug development. Ultimately, Sortera Bio strives to establish a new benchmark for the future of biologics, enabling more efficient and effective therapeutic breakthroughs.
Sortera Bio has raised $10.0M across 1 funding round.
Sortera Bio has raised $10.0M in total across 1 funding round.
Sortera Bio has raised $10.0M across 1 funding round. Most recently, it raised $10.0M Seed in June 2025.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Jun 1, 2025 | $10M Seed | — | Cambridge Innovation Capital, LGT Lightstone, TotalEnergies Ventures | Announced |
Sortera Bio has raised $10.0M in total across 1 funding round.
Sortera Bio's investors include Cambridge Innovation Capital, LGT Lightstone, TotalEnergies Ventures.
Sortera Bio is a biotech startup developing AI-powered platforms for biologics drug discovery. It builds Deep Screening, a breakthrough technology that generates massive sequence-function datasets from single experiments to train machine learning models, enabling faster and more precise identification of novel biologics like antibodies, even for challenging targets such as membrane proteins.[5][6] The company serves pharmaceutical and biotech firms tackling tough drug discovery challenges, solving the critical scarcity of high-quality, unbiased real-world data needed to power AI models for biologics design.[6] Co-founded by protein engineering experts, Sortera Bio raised £7.5 million in pre-seed funding, signaling strong early momentum in the AI-biotech intersection.[5][6]
Sortera Bio was co-founded by Dr. Ben Porebski and Dr. Philipp Holliger, both renowned experts in protein engineering and synthetic biology.[5] The idea emerged from the recognized gap in high-quality data for training AI models in biologics discovery, leading to the creation of their Deep Screening platform, which collects hundreds of millions of sequence-function pairs in one experiment to fuel advanced machine learning.[6] Early traction includes a £7.5 million pre-seed raise, positioning the company to partner with world-leading pharma firms from the outset.[5][6]
Sortera Bio rides the AI-biotech convergence trend, where machine learning accelerates drug discovery amid rising demand for biologics to treat complex diseases.[6] Timing is ideal as AI models hunger for proprietary, high-fidelity data—Sortera's platform fills this void, reducing reliance on synthetic or biased datasets that hinder model performance.[5][6] Market forces like surging biologics R&D (projected to dominate new approvals) and computational biology advances favor its growth, while it influences the ecosystem by enabling pharma partners to de-risk tough targets and shorten timelines from years to months.[6]
Sortera Bio is poised for rapid scaling through strategic pharma partnerships and dataset expansion, potentially licensing Deep Screening widely as AI models mature.[5][6] Trends like multimodal AI integration and membrane protein breakthroughs will amplify its edge, evolving its role from data generator to core enabler in next-gen drug design. As the "game-changing approach" to biologics, it could redefine discovery standards, delivering the high-quality data that powers tomorrow's therapies.[6]
