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§ Private Profile · London, United Kingdom
Protein engineering platform developer integrating AI, robotics, and synthetic biology to design next-generation protein therapeutics for biotech.
LabGenius, based in London, UK, develops an AI-driven protein engineering platform that integrates synthetic biology, machine learning, and robotic automation to design and evolve next-generation protein therapeutics. Their proprietary EVA™ platform enables the discovery and characterization of novel drug molecules, which are then advanced to market by biotech and pharmaceutical partners through R&D programs featuring upfront payments, milestones, and royalties. The company focuses on developing protein therapeutics for diseases like inflammatory bowel disease (IBD) and has secured a deal with Tillotts Pharma AG for IBD drug candidates. LabGenius has raised over $75 million in funding and maintains a team of approximately 50 employees. Key investors include Lux Capital, Obvious Ventures, Felicis Ventures, Atomico, and Kindred Capital. The organization was founded by Dr. James Field.
LabGenius has raised $73.0M across 4 funding rounds.
LabGenius has raised $73.0M in total across 4 funding rounds.
LabGenius has raised $73.0M across 4 funding rounds. Most recently, it raised $44.0M Series B in May 2024.
LabGenius has raised $73.0M in total across 4 funding rounds.
LabGenius's investors include Oliver Hardick, Polygon, Balaji Srinivasan, Jutta Steiner, Ott Kaukver, Irina Elena Haivas, Leila Zegna, LG Corp, Lux Capital, Obvious Ventures, Oliver Sims, Inovia Capital.
LabGenius Therapeutics is a London-based biopharmaceutical company founded in 2012 that develops next-generation protein therapeutics, particularly therapeutic antibodies for solid tumors, using its proprietary EVA™ platform—a machine learning-driven evolution engine integrating AI, robotic automation, and synthetic biology.[1][2][3][5] The platform automates antibody discovery and optimization, enabling rapid co-optimization across multiple properties like selectivity and killing efficacy to address complex design challenges in biologics.[3][5] It serves the biopharmaceutical sector, solving inefficiencies in traditional protein engineering by delivering best-in-class molecules faster; recent momentum includes a £35M ($45M) Series B in June 2024, building on prior $30M raised, with a team of over 50 expanding toward clinical trials.[1][6]
LabGenius was founded in 2012 by James Field, then a PhD student, who envisioned revolutionizing biological molecule discovery through machine learning—a pitch initially dismissed by investors as he was "just a nobody PhD student."[6] Field serves as CEO, with key leaders like Platform Architect Harry Rickerby; the company emerged from his academic work, starting with no traction but persisting through automation and AI integration in labs using high-end DNA sequencers and robots.[1][6] Pivotal moments include early recognition as a "Game Changer" in 2018, steady funding to $30M by 2024, and the £35M Series B to fuel pipeline advancement amid a 12-year path without revenues, focusing on molecule progression over commercialization.[1][2][6]
LabGenius stands out in antibody discovery through these key strengths:
LabGenius rides the AI-biotech convergence trend, accelerating drug discovery amid soaring biologics costs and timelines—critical as solid tumor therapies demand precise, multi-property antibodies that traditional wet-lab methods struggle to engineer.[3][5][6] Timing aligns with post-2020 AI maturity in protein design (e.g., AlphaFold impacts) and investor appetite for ML-driven pharma, as seen in its 2024 funding amid 150 "game-changing" tech deals.[1][2] Market forces like rising cancer prevalence and multispecific antibody demand favor it, while its EVA™ influences the ecosystem by pioneering scalable, data-rich platforms—potentially transforming pharma from artisanal to industrialized, much like automation's rise in the industry.[6]
LabGenius is poised to advance its solid tumor antibody pipeline into clinical trials, likely requiring team growth beyond 50 and further funding to sustain its revenue-free focus on high-value molecules—mirroring NASDAQ biotechs racing to acquisition or IPO.[6] Shaping trends include AI's deepening role in biologics (e.g., generative models for harder targets) and partnerships with big pharma seeking selectivity edges; its influence could expand via platform licensing if EVA™ proves in clinic, cementing it as a leader in faster, smarter protein therapeutics from its 2012 origins.[1][3][5]