Latent Labs, Founded by DeepMind Alum, Launches with $50M to Program Biology

A new startup, Latent Labs, founded by a former Google DeepMind scientist, has just come out of stealth mode with a hefty $50 million in funding. Their mission? To make biology programmable by building AI foundation models that can generate and optimize proteins. They're planning to team up with biotech and pharmaceutical companies to make this happen.

To get why this is a big deal, you gotta understand proteins. They're the workhorses of our cells, doing everything from acting as enzymes and hormones to serving as antibodies. Made up of about 20 different amino acids, these chains fold into 3D structures that determine how they function. Figuring out these shapes used to be a real slog, but DeepMind's AlphaFold changed the game by using machine learning and real biological data to predict the shapes of around 200 million protein structures.

With this kind of data, scientists can better understand diseases, design new drugs, and even create synthetic proteins for new uses. That's where Latent Labs comes in, aiming to let researchers "computationally create" new therapeutic molecules from scratch.

Latent Potential

Simon Kohl, who used to work at DeepMind on the AlphaFold2 team and led their protein design efforts, saw the potential in going solo. He left DeepMind at the end of 2022 to start Latent Labs, which he officially set up in London in mid-2023. Kohl was inspired by the impact of generative modeling in biology and saw an opportunity to focus specifically on protein design.

To make this happen, Latent Labs has hired around 15 people, including some from DeepMind, a senior engineer from Microsoft, and PhDs from the University of Cambridge. They're split between London, where they're working on cutting-edge models, and San Francisco, where they have a wet lab and a computational protein design team.

"Our mission is to make biology programmable, really bringing biology into the computational realm, where the reliance on biological, wet lab experiments will be reduced over time," Kohl explained. This could revolutionize drug discovery, which currently involves tons of experiments and can take years.

The Business of Biology

Latent Labs isn't about developing its own drugs. Instead, they want to speed up and de-risk the early R&D stages for other biopharma, biotech, and life science companies through direct model access or project-based partnerships.

Their $50 million funding includes a $10 million seed round and a $40 million Series A round co-led by Radical Ventures and Sofinnova Partners. Other investors include Flying Fish, Isomer, 8VC, Kindred Capital, Pillar VC, and notable angels like Google's Jeff Dean, Cohere's Aidan Gomez, and ElevenLabs' Mati Staniszewski.

A big chunk of this cash will go towards salaries and hiring more machine learning experts, but they'll also need a lot for infrastructure. "Compute is a big cost for us as well — we're building fairly large models, and that requires a lot of GPU compute," Kohl said. This funding will help them scale their models, grow their teams, and build partnerships.

While there are other startups like Cradle and Bioptimus working on similar goals, Kohl believes we're still early enough in the game that the best approach to decoding and designing biological systems isn't clear yet. "There have been some very interesting seeds planted, [for example] with AlphaFold and some other early generative models from other groups," Kohl said. "But this field hasn't converged in terms of what is the best model approach, or in terms of what business model will work here. I think we have the capacity to really innovate."