New York-based biotech startup Proxima has announced it has raised $80 million in seed funding to transform drug development through innovative technology. Formerly known as VantAI, the company received this investment from a consortium led by DCVC, with participation from NVentures, the venture capital arm of NVIDIA, as well as Braidwell, Roivant, AIX Ventures, Yosemite, Magnetic Ventures, Alexandria Venture Investments, Modi Ventures, and several other strategic and institutional investors.
The funding will primarily support the expansion of Proxima’s data platform, advance machine learning research, and facilitate both internal programs and external collaborations. Proxima is already engaged in partnerships with notable companies, including **Johnson & Johnson**, **Bristol Myers Squibb**, and **Blueprint Medicines**, which is now part of **Sanofi**.
Revolutionizing Drug Discovery
The conventional approach to drug development often revolves around targeting individual faulty proteins to halt their activity. However, Proxima’s strategy addresses the complexity of biological systems by treating proteins as interconnected components within a network. The company focuses on a concept known as induced proximity, creating small molecules that can either bring two proteins together or separate them. This approach allows drugs to act like adapters, modifying cellular functions rather than simply inhibiting them.
By developing medicines that function as molecular matchmakers or separators, Proxima aims to alter protein networks, potentially unlocking treatments for diseases that have resisted traditional methodologies. This shift in perspective has garnered increasing interest in the industry, as proximity-based therapies promise a more sophisticated means of controlling biological processes rather than merely suppressing them.
Harnessing AI for Advanced Drug Design
Central to Proxima’s innovative platform is its software, which draws inspiration from advanced image and video generation technologies. Instead of manipulating pixels, this software operates with molecular structures, enabling the exploration of extensive design spaces to create compounds that precisely fit between proteins. This method effectively turns drug discovery into a three-dimensional puzzle, where the right molecular piece is crucial for stabilizing, disrupting, or rewiring interactions within living cells.
Despite the potential of advanced algorithms, Proxima faces a significant challenge in the form of data limitations. Less than 5% of protein-protein interactions have been structurally mapped, which leaves a considerable portion of cellular biology uncharted. To address this issue, Proxima is deploying its NeoLink technology, a structural proteomics tool designed to generate interaction data at scale. This initiative aims to create a comprehensive dataset, providing what some investors have described as an “unfair data advantage” that could enable programmable protein interactions.
“The development of proximity-based medicines represents one of the most powerful new ways to treat disease, but our progress has been limited by a lack of structural data and effective design tools,” said **Zachary Carpenter**, Co-Founder and CEO of Proxima. “By integrating proteome-scale structural data with cutting-edge AI models, we are establishing a foundation to make these therapies widely accessible.”
**Jason Pontin**, General Partner at DCVC, emphasized the potential of proximity-based therapeutics, noting that they could target previously elusive diseases and “undruggable” proteins. He remarked, “Proxima’s technology unites proteome-scale structural data with state-of-the-art generative AI foundation models. The company’s team is exceptionally positioned to discover and develop a new class of medicines.”
Proxima’s ambitious goals and innovative strategies highlight a significant shift in the biotechnology landscape, presenting promising opportunities for the future of drug discovery. With the recent funding, the company is poised to make impactful advancements in treating complex diseases through a data-driven approach.
