Simon Kohl
Dr. Simon Kohl is the founder and CEO of Latent Labs, a frontier AI lab that enables biotech and pharmaceutical companies to generate and optimize proteins. Simon previously started and co-led DeepMind's protein design team and was a senior research scientist on the Nobel Prize-winning AlphaFold2 project, where he developed the crucial pLDDT confidence quantification system now widely used to predict laboratory success in protein design. At Latent Labs, backed by $50M in total funding from investors including Radical Ventures, Sofinnova Partners, Google Chief Scientist Jeff Dean and CEO of Anthropic Dario Amodei, Simon leads a team innovating frontier models that use cutting-edge generative techniques to computationally create new therapeutic molecules like antibodies and enzymes. The company is focused on enabling partners at scale to tackle challenging targets, develop precision medicines, and accelerate development timelines through their AI protein design platform.
Latent Labs
Senior Leadership AIxBioPharma Luncheon - Inflection Points: Lessons from Computing and Cloud to Catalyze AI in Bio
-
This invite-only luncheon brings together a curated group of senior leaders driving the convergence of AI and BioPharma. Hosted at SynBioBeta 2025, the event is primarily a unique opportunity to network with C-level executives, investors, and researchers shaping the future of AIxBIO. In addition to high-level networking, the luncheon will feature a panel conversation titled Inflection Points: Lessons from Computing and Cloud to Catalyze AI in Bio. Moderated by Celestine Schnugg, Founding Partner at Boom Capital, the session will explore how decades of innovation in computing and cloud infrastructure can inform the next wave of breakthroughs in biology. Joining the conversation are Sandy Pentland, a pioneer in data science and professor at MIT; Richard Socher, CEO of You.com and former Chief Scientist at Salesforce; Simon Kohl, Co-Founder and CEO of Latent Labs; and Nabiha Saklayen, Co-Founder and CEO of Cellino. Together, they will examine how lessons from past technological inflection points can be applied—and adapted—to the emerging era of AI-driven biology. https://lu.ma/a8odlz08
