SAN FRANCISCO--(BUSINESS WIRE)-- Atomic AI, a biotechnology company fusing cutting-edge machine learning with state-of-the-art structural biology to unlock RNA drug discovery, launched today with a $35 million Series A round led by Playground Global, with participation from 8VC, Factory HQ, Greylock, NotBoring, AME Cloud Ventures, and renowned angel investors including GitHub ex-CEO Nat Friedman, Doug Mohr, Curai CEO Neal Khosla, and UC Berkeley professor and Arc Institute Co-founder Patrick Hsu.

The company previously raised a $7 million seed round led by 8VC and joined by Greylock, Factory HQ, AME Cloud Ventures, AIX Ventures, Xu Ventures, Doug Mohr, Antheia, Inc. CEO Dr. Christina Smolke, and Stanford Bioengineering professor Drew Endy.

“To create effective and safer small molecules against undruggable diseases, there is a significant need to develop tools that can accurately predict 3D RNA structures,” said Raphael Townshend, Ph.D., Founder and CEO of Atomic AI. “Atomic AI is oriented at the cutting edge of AI, RNA, and structural biology. We are creating an entirely new field of drug discovery.”

Prominently featured in Science, Atomic AI’s proprietary AI-driven 3D RNA structure engine generates RNA structural datasets, integrating machine learning foundation models with large-scale in-house experimental wet-lab biology to enable the world of RNA drug discovery. In particular, Atomic AI’s technology can discover structured, ligandable RNA motifs at unprecedented speed and accuracy, a critical barrier to current approaches in small molecule drug discovery against RNA. Beyond RNA-targeted molecules, the integrated platform will also enable the design of RNA-based medicines and RNA tools.

“To date, there has been little advancement in understanding the intricate and complex structure of RNA,” said Jory Bell, General Partner at Playground Global. “We are excited to support Raphael, the impressive interdisciplinary Atomic AI team, and the company’s technology, which has the potential to vastly improve RNA structure prediction and develop a new generation of RNA-targeting medicines to tackle diseases that were previously untreatable.”

“There are well-known RNA sequences that play a critical role in driving disease; however, current technologies lack the RNA-structure modeling capabilities necessary to create confidence in RNA-targeting drug discovery,” said Gene Yeo, Professor of Cellular and Molecular Medicine at the University of California San Diego (UCSD), an expert in RNA biology and member of Atomic AI’s advisory board. “Atomic has created a sophisticated and integrated AI engine that will transform the discovery and development of RNA-targeted medicines.”

About the Atomic AI Platform
Atomic AI’s proprietary Platform for AI-driven RNA Structure Exploration (PARSE) is an AI-driven 3D RNA structure discovery engine. By leveraging RNA foundation models that operate directly at the atomic level with custom data, this AI-driven RNA structure technology can discover novel structural targets across transcripts of interest, thereby enabling the drugging of the transcriptome, and generate new structural motifs for use in RNA medicines and tools, allowing for their design to desired specifications.

About Atomic AI
Atomic AI is an emerging biotechnology company exploiting the cutting-edge fusion of artificial intelligence and structural biology to unlock RNA drug discovery. Based on research prominently featured in Science, Atomic AI’s proprietary R&D platform leverages state-of-the-art deep learning foundation models integrated into a virtuous cycle with purpose-designed, in-house wet-lab assays, to discover and design proprietary 3D RNA structural datasets. Backed by an interdisciplinary team of machine learning researchers, engineers, and experimental biologists, as well as strategic scientific advisers and world-class investors, Atomic AI is leading the way in AI-augmented structural biology and transforming the design of RNA-targeted and RNA-based medicines to treat undruggable diseases. To learn more, visit atomic.ai and engage with us on LinkedIn and Twitter.

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