Latent Labs Emerges with $50M to Revolutionize Drug Discovery Using AI

Latent Labs raises $50M to develop new proteins with AI - SiliconANGLE

Latent Labs Inc., an artificial intelligence startup focused on the healthcare sector, launched today with $50 million in initial funding. Radical Ventures and Sofinnova Partners jointly led the investment. They were joined by more than a half dozen other backers including Google LLC chief scientist Jeff Dean. Cohere Inc. Chief Executive Officer Aidan Gomez, a former researcher at the search giant who co-invented the Transformer architecture, participated as well. Latent Labs is led by CEO Simon Kohl, who previously worked at Google parent Alphabet Inc.'s DeepMind machine learning lab. He was part of the team that developed DeepMind's groundbreaking AlphaFold2 neural network. The algorithm, which helps researchers understand the shape of proteins, earned Google scientists Demis Hassabis and John Jumper one half of the 2024 Nobel Prize for Chemistry. Proteins, the basic building blocks of life, can twist and fold into various shapes. The configuration of a protein directly influences its behavior. AlphaFold2 significantly reduces the amount of time and effort required to determine proteins' shape, which enables scientists to speed up medical research. Latent Labs hopes to take computational biology one step further. The company is developing foundation AI models that don't merely predict the shape of proteins, but rather generate new protein designs from scratch. It hopes to use those designs to support the development of new medicines. Latent Labs is focusing its efforts on two types of proteins: antibodies and enzymes. Antibodies help the immune system neutralize harmful particles. Enzymes, meanwhile, are widely used in pharmaceutical manufacturing because they speed up chemical reactions. "Every biotechnology or pharmaceutical company wants to be at the forefront of technology to find the best therapeutic molecules, yet not all are in a position to develop the most advanced AI models for the job," Kohl said. "That's where Latent Labs comes in." A job posting on Latent Labs' website indicates that it's building custom software to speed up its AI model development efforts. In particular, the company hopes to automate the so-called hyperparameter search phase of the workflow. Hyperparameters are settings that influence how an AI model processes data. Those settings define details such as the number of artificial neurons in a model and the way those neurons coordinate their work. Developers typically don't search for the optimal combination of hyperparameters manually, but rather use algorithms that can quickly try a large number of variations. Latent Labs is building a wet lab, a type of laboratory optimized to process chemicals, in order to test the proteins developed by its AI models. The lab will also have a second purpose: generating research data that the company can use to fine-tune its AI models. Kohl told Forbes that the company has already "seen very good success with our own models." Latent Labs plans to commercialize its models by making them available to researchers for use in drug development. In addition, the company intends to ink "project-based partnerships" with drugmakers that will see it earn commissions when those companies meet key project milestones. Latent Labs will use its new funding to hire more AI researchers and expand its graphics card cluster.

Latent Labs emerges from stealth to accelerate drug discovery

Latent Labs pushes the frontiers of generative biology, CEO Simon Kohl said. Latent Labs, a start-up building generative artificial intelligence (AI) models to accelerate drug discovery and research has emerged from stealth with $50m in total funding. The infusion includes a $40m Series A funding co-led by Radical Ventures and Sofinnova Partners, with the participation of Flying Fish, Isomer, as well as its existing investors 8VC, Kindred Capital and Pillar VC. Angel investors including Google's chief scientist Jeff Dean, AI tech company Cohere's founder Aidan Gomez and the founder of ElevenLabs Mati Staniszewski also took part in the funding round. The start-up was founded in 2023 by Dr Simon Kohl, a former co-lead at Google DeepMind's protein design team as well as a senior research scientist at DeepMind's AlphaFold2 - a Nobel prize winning project. According to the company co-headquartered in London and San Francisco, Latent Labs is advancing the developments made by AlphaFold's application of machine learning technology, which improved protein structure prediction. Now, the start-up is aiming to empower researchers to computationally create new therapeutic molecules, such as such as antibodies or enzymes to "open new paths to personalised medicines". Moreover, scientists working with the start-up's lab can utilise its AI-driven research platform to design proteins with more stable molecular features, expediting drug development timelines and raising clinical success rates, the company said. The life sciences industry in Europe is booming, having seen $8bn in venture capital investments in just 2024, while the first quarter of this year has already seen investments of more than $1.2bn to date. "Every biotechnology or pharmaceutical company wants to be at the forefront of technology to find the best therapeutic molecules, yet not all are in a position to develop the most advanced AI models for the job. That's where Latent Labs comes in," said Kohl, who is also the start-up's CEO. "We push the frontiers of generative biology, giving our partners instant access to tools that accelerate their drug design programs." Aaron Rosenberg, a partner at Radical Ventures is confident in Latent Labs' potential to develop new protein designs. He said: "Such a capability has never before been possible, one which can benefit humanity in such a profound way. Accelerating the development of more effective cures for disease, Latent is at the vanguard of innovation in computational biology, and we are excited to join them on this journey." AI has had a major impact in drug discovery techniques in recent years, with major tech companies, including AMD, Nvidia and AWS, collaborating together and investing in drug creation companies to boost their discovery power. While start-ups including Basecamp Research and Bioptimus have raised tens of millions to develop dedicated AI models trained on specific natural sciences data. Sofinnova Partners, the VC which co-led Latent Lab's Series A, is also an investor in Bioptimus. Don't miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic's digest of need-to-know sci-tech news.

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

A new startup founded by a former Google DeepMind scientist is exiting stealth with $50 million in funding. Latent Labs is building AI foundation models to "make biology programmable," and it plans to partner with biotech and pharmaceutical companies to generate and optimize proteins. It's impossible to understand what DeepMind and its ilk are doing without first understanding the role that proteins play in human biology. Proteins drive everything in living cells, from enzymes and hormones to antibodies. They are made up of around 20 distinct amino acids, which link together in strings that fold to create a 3D structure, whose shape determines how the protein functions. But figuring out the shape of each protein was historically a very slow, labor-intensive process. That was the big breakthrough that DeepMind achieved with AlphaFold: it meshed machine learning with real biological data to predict the shape of some 200 million protein structures. Armed with such data, scientists can better understand diseases, design new drugs, and even create synthetic proteins for entirely new use-cases. That is where Latent Labs enters the fray with its ambition to enable researchers to "computationally create" new therapeutic molecules from scratch. Simon Kohl (pictured above) started out as a research scientist at DeepMind, working with the core AlphaFold2 team before co-leading the protein design team and setting up DeepMind's wet lab at London's Francis Crick Institute. Around this time, DeepMind also spawned a sister company in the form of Isomorphic Labs, which is focused on applying DeepMind's AI research to transform drug discovery. It was a combination of these developments that convinced Kohl that the time was right to go it alone with a leaner outfit focused specifically on building frontier (i.e., cutting-edge) models for protein design. So at the tail-end of 2022, Kohl departed DeepMind to lay the foundations for Latent Labs, and incorporated the business in London in mid-2023. "I had a fantastic and impactful time [at DeepMind], and became convinced of the impact that generative modelling was going to have in biology and protein design in particular," Kohl told TechCrunch in an interview this week. "At the same time, I saw that with the launch of Isomorphic Labs, and their plans based on AlphaFold2, that they were starting many things at once. I felt like the opportunity was really in going in a laser-focused way about protein design. Protein design, in itself, is such a vast field, and has so much unexplored white space that I thought a really nimble, focused outfit would be able to translate that impact." Translating that impact as a venture-backed startup involved hiring some 15 employees, two of whom were from DeepMind, a senior engineer from Microsoft, and PhDs from the University of Cambridge. Today, Latent's headcount is split across two sites -- one in London, where the frontier model magic happens, and another in San Francisco, with its own wet lab and computational protein design team. "This enables us to test our models in the real world and get the feedback that we need to understand whether our models are progressing the way we want," Kohl said. While wet labs are very much on the near-term agenda in terms of validating Latent's technology's predictions, the ultimate goal is to negate the need for wet labs. "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 said. That highlights one of the key benefits to "making biology programmable" -- upending a drug-discovery process that currently relies on countless experiments and iteration that can take years. "It allows us to make really custom molecules without relying on the wet lab -- at least, that's the vision," Kohl continued. "Imagine a world where someone comes with a hypothesis on what drug target to go after for a particular disease, and our models could, in a 'push-button' way, make a protein drug that comes with all of the desired properties baked in." In terms of business model, Latent Labs doesn't see itself as "asset-centric" -- meaning it won't be developing its own therapeutic candidates in-house. Instead, it wants to work with third-party partners to expedite and de-risk the earlier R&D stages. "We feel the biggest impact that we can have as a company is by enabling other biopharma, biotechs and life science companies -- either by giving them direct access to our models, or supporting their discovery programs via project-based partnerships," Kohl said. The company's $50 million cash injection includes a previously unannounced $10 million seed tranche, and a fresh $40 million Series A round co-led by Radical Ventures -- specifically, partner Aaron Rosenberg, who was formerly head of strategy and operations at DeepMind. The other co-lead investor is Sofinnova Partners, a French VC firm with a long track-record in the life sciences space. Other participants in the round include Flying Fish, Isomer, 8VC, Kindred Capital, Pillar VC, and notable angels such as Google's chief scientist Jeff Dean, Cohere founder Aidan Gomez, and ElevenLabs founder Mati Staniszewski. While a chunk of the cash will go toward salaries, including those of new machine learning hires, a significant amount of money will be needed to cover infrastructure. "Compute is a is a big cost for us as well -- we're building fairly large models I think it's fair to say, and that requires a lot of GPU compute," Kohl said. "This funding really sets us up to double-down on everything -- acquire compute to continue scaling our model, scaling the teams, and also starting to build out the bandwidth and capacity to have these partnerships and the commercial traction that we're now seeking." DeepMind aside, there are several venture-backed startups and scaleups looking to bring the worlds of computation and biology closer together, such as Cradle and Bioptimus. Kohl, for his part, thinks that we're still at a sufficiently early stage, whereby we still don't quite know what the best approach will be in terms of decoding and designing biological systems. "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."

Ex DeepMind scientist launches AI drug discovery venture

A scientist who helped build DeepMind's Nobel Prize-winning protein prediction programme has raised $50mn to launch a company to discover new drugs. Simon Kohl has founded Latent Labs to capitalise on his experience working on the AI-powered AlphaFold2 system, which solved an important problem for life sciences researchers by allowing the prediction of the 3D structure of proteins based on their chemical composition. Latent Labs, which has offices in London and San Francisco, will work with the pharmaceutical industry to design synthetic proteins, which could be used in drugs such as antibody treatments. Kohl said generative AI, which creates new content, had the potential to change how drugmakers operate by making biology "programmable". "In a perfect world, the dream of purely computational drug discovery comes to life," he described. "You tell me, this is the sort of disease you're going after. Maybe there's a target protein that you have in mind. And at a push of a button, we can generate candidates that meet all of the criteria you care about, which de-risks the steps that come after, shaves time off the process, and at the end of the day, will yield better drugs, faster." Many other start-ups are also trying to create drugs using artificial intelligence and most plan to partner with pharmaceutical companies on any drugs they do discover. Latent Labs is pursuing a different model: it wants to be a service provider to pharmaceutical companies, providing a generative AI platform that they can use. Its aim is to work with drugmakers, many of which have built their own AI teams, to use the technology to cut short the long and expensive process of discovering and developing drugs. DeepMind has also spun out its own drug discovery company, Isomorphic Labs. Kohl said Isomorphic is following the more common business model of partnering with pharma companies, and is taking a broader approach beyond just proteins, including looking for the small molecules that form the basis of many drugs. The fundraising was co-led by Radical Ventures, which specialises in AI software companies, and European healthcare venture firm Sofinnova Partners. Other investors include Jeff Dean, Google's chief scientist, and Aidan Gomez, one of the authors of the research paper that led to the creation of ChatGPT. Aaron Rosenberg, a partner at Radical Ventures who also used to work at DeepMind, said Latent Labs had hired an "all star" team from companies including Microsoft, Google, and Altos Labs, a biotech focused on longevity. He expects that the company's model, which is already "amazingly capable" will improve dramatically. "This is a whole new world of computational biology," he said.