Latent Labs Emerges from Stealth with $50 Million to Revolutionize Protein Design
Introduction
Latent Labs, a pioneering startup founded by a former DeepMind scientist, has emerged from stealth with an impressive $50 million in funding. The company aims to transform the field of biology by developing cutting-edge artificial intelligence (AI) foundation models that "make biology programmable." By partnering with biotech and pharmaceutical companies, Latent Labs seeks to revolutionize protein generation and optimization for therapeutic applications.
The Role of Proteins in Biology
To comprehend the significance of Latent Labs’ mission, it is essential to understand the crucial role that proteins play in human biology. Proteins are the building blocks of life, driving every aspect of cellular activity, from enzymes and hormones to antibodies. Composed of a sequence of amino acids, proteins fold into unique three-dimensional structures that determine their function.
Historically, determining the shape of proteins has been a painstaking and time-consuming process. However, DeepMind’s groundbreaking AlphaFold algorithm has introduced a paradigm shift. By combining machine learning with real-world biological data, AlphaFold can predict the structure of hundreds of millions of proteins.
DeepMind’s Impact on Protein Design
Armed with this data, scientists can gain deeper insights into diseases, design novel drugs, and even create synthetic proteins for innovative applications. Latent Labs capitalizes on these advancements, aspiring to empower researchers with the ability to "computationally create" therapeutic molecules from scratch.
Simon Kohl, Latent Labs’ founder, played a pivotal role at DeepMind, contributing to AlphaFold2 and establishing the company’s wet lab. Inspired by the transformative potential of AI in protein design, Kohl recognized the need for a focused venture focused on pushing the boundaries of protein design.
Latent Labs’ Mission: Making Biology Programmable
Latent Labs’ mission is to "make biology programmable," effectively bringing biology into the computational realm. By reducing reliance on wet lab experiments, the company aims to accelerate drug discovery and therapeutic development.
Technology and Approach
Foundation Models and Wet Labs
Latent Labs develops advanced foundation models for protein design. These models leverage vast amounts of data to learn the underlying principles of protein structure and function.
To validate the predictions generated by its models, Latent Labs utilizes wet labs where proteins can be synthesized and tested in a real-world environment. This iterative approach ensures that models are continuously refined and optimized.
Ultimate Goal: Negating the Need for Wet Labs
While wet labs are crucial for validating the company’s technology in the short term, the ultimate vision is to make their use obsolete. Latent Labs envisions a world where scientists can design protein drugs "in a push-button way," eliminating the need for countless wet lab experiments and iterations that can take years.
Business Model
Partnerships and Licensing
Latent Labs does not aim to develop its own therapeutic candidates in-house. Instead, the company seeks to collaborate with third-party partners to expedite and de-risk early research and development (R&D) stages.
By providing direct access to its models or engaging in project-based partnerships, Latent Labs empowers biopharmaceutical and biotech companies to harness its technology for their discovery programs.
Funding and Investors
Latent Labs’ $50 million funding round includes a previously unannounced $10 million seed tranche and a fresh $40 million Series A round. The round was co-led by Radical Ventures and Sofinnova Partners, renowned investors in the technology and life sciences sectors.
Other notable investors include Flying Fish, Isomer, 8VC, Kindred Capital, Pillar VC, and prominent angel investors such as Google’s chief scientist Jeff Dean and Cohere founder Aidan Gomez.
Market Landscape and Competition
While DeepMind has made significant contributions to protein design, several venture-backed startups and scale-ups, such as Cradle and Bioptimus, are also pursuing the convergence of computation and biology.
Simon Kohl emphasizes that the field is still in its early stages, and the optimal approach to decoding and designing biological systems remains uncertain. Latent Labs believes that its innovative models and partnership-driven business model position it to lead the way in this rapidly evolving landscape.
Conclusion
Latent Labs’ emergence from stealth marks a transformative chapter in the field of protein design. Armed with cutting-edge AI foundation models and a mission to "make biology programmable," the company has the potential to revolutionize drug discovery, therapeutic development, and our understanding of biological systems as a whole. Its strategic partnerships and impressive funding provide a solid foundation for Latent Labs to continue pushing the boundaries of AI and biology, unlocking new possibilities for human health and scientific advancement.
