35. Simon Kohl
- Founder & CEO, Latent Labs
From Nobel Prize-winning protein prediction to breakthrough drug design, Simon Kohl has positioned himself at the forefront of A.I.’s transformation of biology. He co-led Google DeepMind’s protein design team and was a senior research scientist on DeepMind’s AlphaFold2, the project that earned Demis Hassabis and John Jumper the 2024 Nobel Prize in Chemistry. “Having co-developed AlphaFold2, I’ve seen firsthand how A.I. can solve incredibly complex problems,” Kohl tells Observer.
Before leaving DeepMind, Kohl built AlphaFold2’s widely used uncertainty prediction system “pLDDT” and set up DeepMind’s wet lab at London’s Francis Crick Institute. When Kohl realized it was possible to “move beyond just predicting biological structures to actually designing them from scratch,” Kohl decided to found Latent Labs. “We were at an inflection point where generative A.I. could make biology programmable.” In 2024, Latent Labs was one of the early-stage startups to receive support from AWS through its Generative A.I. Accelerator.
In February, Latent Labs raised $50 million in venture capital funding. Angel investors include Google Chief Scientist Jeff Dean, Cohere founder Aidan Gomez and ElevenLabs founder Mati Staniszewski.
In July, the company launched LatentX, achieving 91 percent to 100 percent hit rates for macrocycles and 10 percent to 64 percent for mini-binders across seven therapeutic targets in wet lab experiments. Unlike traditional methods that predict existing structures, LatentX simultaneously designs the molecular sequence and 3D structure of proteins in real-time, following atomic-level physical rules to create entirely novel molecules. “We’re not just understanding nature anymore, we’re becoming capable of authoring it with precision,” he says. “Scientists achieve in 30 candidates what previously required testing millions, turning months of experiments into seconds of computation.” Traditional drug discovery hit rates are typically below 1 percent, Kohl explains.
Bringing experience from DeepMind, Microsoft, Google, Stability AI, Exscientia, Mammoth Bio, Altos Labs and Zymergen, Kohl’s team is prioritizing oncology, autoimmune diseases and rare genetic disorders—areas where conventional drug discovery faces significant challenges. The company is particularly focused on macrocycles, which combine the precision of biologics with the oral deliverability of small molecules. In direct laboratory comparisons, Latent Labs has outperformed results from major technology companies and leading academic institutions, leveraging their team’s AlphaFold experience combined with enterprise-grade platform engineering.
Rather than developing proprietary medicines, Latent Labs licenses its technology through a web-based platform, making advanced A.I. accessible to academic institutions, biotech startups and pharmaceutical companies. While making the technology broadly accessible, Latent Labs maintains strict biosafety protocols, actively engages with regulators on dual-use concerns, and validates all computational designs in its physical laboratory to ensure real-world safety.
“We envision a future where effective therapeutics can be designed entirely in a computer, much like how space missions or semiconductors are designed today,” he says. Kohl acknowledges the growing complexity of biological systems and the need for equally sophisticated safety frameworks as these powerful generative tools become more widespread. “Biology remains fundamentally messy,” he says. “A.I. currently amplifies our capabilities, but it still requires deep scientific intuition to ask the right questions and interpret what the models tell us.”
