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Self-Driving-Labs (2/3) — The Rise of In-House SDLs in Antibody Discovery

Beyond the self-driving laboratories (SDLs) developed by academia and research institutions, the industry has inevitably joined the fray…

不專業學術閒聊 · 2026-06-12 15:03 · 0 claps · 1.5 min read
#self-driving-lab #insitro #bighat-biosciences #absci #eli-lilly
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Self-Driving-Labs (2/3) — The Rise of In-House SDLs in Antibody Discovery

Beyond the self-driving laboratories (SDLs) developed by academia and research institutions, the industry has inevitably joined the fray. After all, drug development is all about speed.

Currently, most SDLs are primarily applied to materials or small-molecule drugs. Although biologics have become increasingly prominent over the past decade or so, their manufacturing processes remain far more complex than those of small molecules. Nevertheless, several biotech companies have already started adopting SDLs. Additionally, major pharmaceutical companies are partnering with AI/ML firms to integrate SDL capabilities into their existing automated robotic systems. For instance, at the J.P. Morgan Healthcare Conference (JPM) this January, Eli Lilly and NVIDIA announced a collaboration to build an AI factory.

Below is a brief introduction to companies developing antibody drugs using their own SDLs.

🌐 LabGenius Therapeutics

London-based LabGenius Therapeutics (founded in 2012) combines AI, robotics, and synthetic biology to engineer next-generation therapeutic antibodies, with a focus on multispecific formats. Its proprietary EVA™ platform is a fully closed-loop SDL.

EVA™ Platform

EVA™ is a highly automated, closed-loop SDL that integrates machine learning (ML), robotics, and synthetic biology to rapidly generate next-generation antibodies. Its Design–Build–Test–Learn cycle consists of two main components:

  • Dry Lab: ML models trained on experimental data to predict and design antibodies.
  • Automation Lab: Robotic systems that produce and test up to 2,300 multispecific antibodies per run.

Experimental results are fed back into the ML models for optimization, enabling continuous cycles of design, production, and testing. Each cycle takes less than 6 weeks, significantly accelerating the antibody development process compared to traditional approaches.

The platform supports a wide range of antibody modalities, including T-cell engagers (TCEs), antibody–drug conjugates (ADCs), NK-cell engagers, TCR-based engagers, and radioconjugates.

One of their lead candidates, LGTX-101, designed by EVA™, is a Nectin-4 × CD3 bispecific TCE currently advancing toward IND submission, with demonstrated >70,000-fold tumour selectivity.

Current updates

  • The company has raised multiple rounds of funding, including a £35 million Series B round in 2024.
  • In December 2025, LabGenius announced its second collaboration with Sanofi to optimize anti-inflammatory NANOBODY® therapeutics using the EVA™ platform.

Read full article here: https://lindakang.github.io/InsideScience/?post=2026-05-06-antibody-companies-building-their-own-sdls

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