Pioneering the Largest Foundation Model to Transform RNA Research: An Interview with Brendan Frey

These developments are accompanied by strategic hires of top-tier talent: Dr. Radu Dobrin, formerly with Pathos AI and Tempus AI, as Chief Technology Officer to drive advancements in Deep Genomics' proprietary AI platform, BigRNA; Dr. Greg Hoffman, previously at Arbor Biotechnologies, as Chief Scientific Officer to lead efforts in applying AI in therapeutic discovery; Joel Shor, from Verily Life Sciences, as Vice President and Head of Machine Learning to enhance the company’s machine learning capabilities; and Clive Bertram, from ObsEva, as Chief Business Officer to focus on expanding the company’s commercial presence and strategic development.

In this interview, we sit down with Brendan Frey, Founder and CIO of Deep Genomics, to delve into his vision for the future of RNA therapeutics and the integral role of AI in advancing biological research. Frey discusses how the recent expansions and new executive hires will enhance Deep Genomics' capabilities in decoding RNA biology and designing innovative therapeutics. He also shares insights into how their AI platform, BigRNA, is set to transform genomic R&D, reduce risks, and accelerate the development of new treatments.

Andrii: With the increasing role of AI in biotech, how do you see Deep Genomics positioning itself within the industry? What sets your approach apart from other companies working on AI-driven drug discovery and development?

Brendan: Productivity in R&D for the Life Sciences industry continues to be its greatest challenge. By pioneering a novel new approach to early stage R&D, we’re charting a unique path as the leaders of a new category of TechBios, and guiding improved genomic R&D as a result.

Whereas the tech world has a rich open source history, this ethos is relatively new to the pharmaceutical industry. Organizations that are built from the ground up with technology as the driving force enable seamless integration and collaboration between biologists, chemists, and AI researchers. 

We are placing AI at the forefront of genomic R&D. Since 2018, we’ve coined terms at Deep Genomics such as ‘programmable medicines’, ‘digital medicines’ and ‘AI-biology multilingual teams’, which are now commonly used terms.  Tech is not the new factor here – but by moving forward with our TechBio approach, we can more readily acknowledge AI’s vital role in the pharma industry.

Andrii: RNA biology is a complex and rapidly evolving field. What initially drew you to focus on RNA, and why do you believe it holds such significant potential for therapeutic development?

Brendan: We often say RNA is essentially the ‘software of biology’, making it the ideal place to intervene with AI. With RNA's optimal fundamental design, the availability of the data available, and big steps forward made in computing power – RNA holds massive potential for transforming not just the drugs in the market – but the way we think about pharma and R&D. 

Drugs aligned with proteins or biologics are neither well-matched to a computer, nor AI. RNA, however, is fundamentally digital - it’s made up of a sequence of letters. What could be better matched to a computer than a sequence of letters? Not only that, but unlike its DNA editing and gene therapy counterparts, RNA therapy enables tunability and reversibility, offering unique advantages in specific therapeutic settings.