CNSE Partnering with DeepSeq on Generative AI for Drug Research
ALBANY, N.Y. (Nov. 21, 2024) — University at Albany Professor of Nanoscale Science and Engineering Susan Sharfstein is partnering with the startup firm DeepSeq.AI on a new National Science Foundation (NSF) grant to advance AI-driven drug discovery.
Funded through an NSF Small Business Innovation Research (SBIR) Phase I grant of nearly $275,000, the project will support the development of DeepSeq's proprietary artificial intelligence (AI) platform, which is focused on empowering pharmaceutical companies to design innovative, functional and manufacturable large molecule drugs.
DeepSeq’s platform uses an explainable Generative AI approach, which optimizes multiple drug properties through a combination of machine learning and highly scalable, proprietary wet-lab screening.
“In an era where biopharmaceuticals move towards complex molecules under cost-reduction pressures, understanding multifunctional protein optimization is crucial,” said Sharfstein. “We're excited to be working with DeepSeq to push the boundaries with innovative solutions that advance the field.”
The NSF’s SBIR program supports the development and initial steps towards translation of groundbreaking technologies with potential for substantial societal and economic contributions.
"The NSF SBIR Phase I grant proves that we are using an innovative approach in a groundbreaking manner, and our platform is poised to have a significant impact on AI-driven drug discovery,” said DeepSeq CEO Andrew Chang. “Unlike many competitors, we focus on generating substantial, reliable customized training data for each project to model diverse protein functions effectively."
DeepSeq aims to utilize the SBIR grant to significantly expand its dataset, enhancing its algorithm's ability to explore a broader protein functional space.
"The NSF SBIR Phase-I grant is set to elevate our foundational model, addressing critical challenges faced by the pharma and biotech industries,” said Chang.
Sharfstein’s lab focuses on understanding the role of culture conditions and cell physiology on use of living systems for industrially relevant processes. The lab has several ongoing projects, including exploring the use of mammalian cell systems for the production of therapeutic proteins and carbohydrates and utilizing nanotechnology for high-throughput RNA delivery and novel biosensors for bioreactors.
“Our research addresses key bioengineering challenges, including cellular productivity, DNA methylation, and protein glycosylation, to improve therapeutic outcomes. We innovate in tissue engineering and regenerative medicine, developing novel treatments for conditions like salivary gland dysfunction and glaucoma,” said Sharfstein. “Our lab also investigates ways to interface living systems with electronic and photonic devices to create biohybrid systems and advance cell therapies. Collaborating with academic and industry partners, our lab is committed to driving impactful advancements in biotechnology and medicine.”
Sharfstein has previously received more than $1.5 million in research awards in the last decade, Including a $250,000 grant from NSF In 2021.
“As engineers, our ultimate goal with research is to have what we learn in the lab translate to real world applications. This award shows the advancement that is possible when small companies partner with academic institutions and federal funding through NSF,” said College of Nanotechnology, Science, and Engineering Dean Michele J. Grimm. “The overarching goal of the NSF SBIR program is to foster economic growth and job creation – and I look forward to seeing how this collaboration can add to the economic development strength of the US in addition to improving human health.”
About DeepSeq.AI
DeepSeq.AI is revolutionizing AI-driven drug discovery by combining novel high-throughput wet lab assays with explainable generative AI to design biologics optimized for multiple key functions. DeepSeq.AI's proprietary platform generates massive-scale protein function data and models protein "grammar," enabling the design of therapeutics optimized for conditional binding, manufacturability, efficacy and more. Validated by paying customers, including several top global biopharma companies, and protected by a granted patent, DeepSeq.AI's technology is setting new standards in biologics discovery. DeepSeq.AI's approach has been further endorsed by investments from leading biotech accelerators, such as Merck DSS and UC Berkeley SkyDeck, as well as a prestigious NSF SBIR grant. Together, DeepSeq.AI is accelerating the future of biologics development.