DeepSeq.AI (DeepSeq), a leading startup in artificial intelligence for protein drug discovery, proudly announces the receipt of a National Science Foundation (NSF) Small Business Innovation Research (SBIR) Phase I grant of approximately $275,000. The highly selective NSF SBIR program supports the development of groundbreaking technologies with potential for substantial societal and economic contributions.
The SBIR grant recognizes the value of DeepSeq's proprietary AI platform, which empowers pharmaceutical companies to design innovative, functional, and manufacturable large molecule drugs. The platform uses an explainable Generative AI approach, optimizing multiple drug properties through a combination of machine learning and highly scalable, proprietary wet-lab screening.
DeepSeq stands out by not only conceptualizing protein "grammar" to enhance drug discovery outcomes—including conditional binding and manufacturability—but also by already possessing a validated commercial product (secured by a granted patent), which is supported by several biotech customers, including a top 10 pharmaceutical client. The firm has also been validated and bolstered by investments from prestigious biotech accelerators such as the Merck Digital Sciences Studio and UC-Berkeley’s Skydeck.
DeepSeq CEO Andrew Chang, Ph.D., an AI expert with recognition from numerous machine learning competitions, including Roche's machine learning competition, notes:
"The NSF SBIR Phase I grant proves that we are using a highly innovative approach in a groundbreaking manner. Our platform is poised to have a significant impact on AI-driven drug discovery. Unlike many competitors, we focus on generating substantial, reliable customized training data for each project to model diverse protein functions effectively."
The SBIR grant will enable DeepSeq.AI to significantly expand its datasets, and to enhance its AI-driven algorithm's ability to explore a broader protein functional space.
"The NSF SBIR Phase-I grant will allow us to elevate our foundational model, addressing critical challenges faced by the pharma and biotech industries, building on and supplementing advancements like AlphaFold 3" adds Dr. Chang.
DeepSeq will be closely collaborating with Susan Sharfstein, Ph.D, Professor of Nanoscale Science and Engineering at the State University of New York-Albany (SUNY-Albany) on the project related to the SBIR grant. Professor Sharfstein further notes:
"In an era where biopharmaceuticals move towards complex molecules under cost-reduction pressures, understanding multifunctional optimization is crucial. We're excited to be working with DeepSeq to push the boundaries with innovative solutions that advance the protein drug discovery field."
