Founded by DeepMind alumnus, Latent Labs launches with $50M to make biology programmable

Latent Labs, founded by DeepMind alum Simon Kohl, launches with $50M to revolutionize protein design using AI to make biology programmable.

: Latent Labs aims to create programmable biology through AI, inspired by DeepMind's AlphaFold technology. Founded by Simon Kohl, a former DeepMind scientist, Latent Labs is supported with a $50 million fund, bringing together a skilled team from prestigious institutions. The new venture focuses on transforming the drug discovery process by enabling computational creation of therapeutic molecules, reducing reliance on labor-intensive wet labs. While the company collaborates with biotech and pharmaceutical firms for R&D advancement, substantial investment is allocated for compute resources to support large model development.

Latent Labs, recently launched from stealth with a substantial $50 million funding, seeks to make biology programmable. The startup, led by former DeepMind scientist Simon Kohl, intends to leverage AI to optimize and generate proteins, partnering primarily with biotech and pharmaceutical companies. By bringing AI foundation models into the mix, Latent Labs aims to simplify and accelerate the process of understanding and creating new proteins, influencing drug discovery and treatment development. The foundation of this initiative rests on the significant strides made by DeepMind's AlphaFold, which successfully used machine learning to predict the structure of 200 million protein structures. AlphaFold's technology combined with new ambitions in computational biology highlights Latent Labs' plan to innovate within the life sciences sector.

Simon Kohl's background with DeepMind, including forming part of the AlphaFold2 team and establishing a wet lab at London's Francis Crick Institute, signifies his deep insights into both AI and biology. This experience led him to see a timely opportunity to create a more focused and agile entity dedicated to cutting-edge protein design. As a nimble startup, Latent Labs aims to develop frontier models for protein design, founded in London and boasting collaboration from key scientific figures such as a former Microsoft engineer and PhDs from Cambridge. The company has already attracted noteworthy investors, including Radical Ventures and Sofinnova Partners, along with support from industry leaders like Google’s chief scientist Jeff Dean.

The business strategy of Latent Labs is to empower other biopharma and biotech companies by providing access to their models or assisting in discovery programs. Their approach is not asset-centric; instead, they aim to aid third-party R&D. Kohl expresses his vision of creating a world where biology is seamlessly integrated with computational advancements, eventually leading to decreased dependency on wet lab testing. This notion resonates with the overarching goal to enhance drug discovery processes, making them faster and more tailored.

A significant portion of the $50 million funding is earmarked for computational infrastructure, underlining the intensive resource demands of developing large-scale AI models. Compute costs, driven by the need for GPU power, represent a key investment area as Latent Labs seeks to push the boundaries of biological research and secure commercial traction. While wet labs are currently necessary, the startup's vision encompasses fully computational drug design processes that eliminate or minimize the need for physical experimentation.

Amidst the growing field of computational biology, which includes other startups like Cradle and Bioptimus, Latent Labs is poised at an early stage where diverse methods and business models are still being tested. In this dynamic landscape, Simon Kohl remains confident about Latent Labs' potential to innovate and redefine the intersection of AI and biological sciences. This venture highlights a transformative direction in making biology as programmable and efficient as computational systems, aiming to unlock a new era of biotechnology.

Sources: TechCrunch, Latent Labs, DeepMind

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