10x Science, which builds frontier AI for molecular-level protein characterization across the life sciences, today announced the closing of its $4.8M seed round led by Initialized Capital. The oversubscribed round includes investments from Y Combinator, Civilization Ventures, Founder Factor, and a group of strategic angel investors. Starting with drug development, the company's platform delivers automated, explainable molecular insights in minutes where current tools and manual workflows require months. With tens of thousands of biologic drugs in active development worldwide and regulatory demands for molecular characterization intensifying, 10x Science is unlocking a new category at the intersection of AI and the life sciences.

Protein characterization is foundational to drug development. Every biologic therapeutic, from cancer immunotherapies to gene therapies, must be characterized at the molecular level to determine whether it is safe, effective, and manufacturable. Today, this work depends on specialized scientists spending weeks or months manually interpreting complex mass spectrometry data using tools that have not fundamentally changed in decades.

The pharmaceutical industry is developing more complex protein therapeutics than ever before, and the demand for characterization is growing far faster than the supply of experts who are trained for it. The 10x Science platform addresses this bottleneck with a purpose-built AI architecture that reasons across hundreds of thousands of spectra, identifies molecular forms and chemical modifications, and delivers comprehensive, explainable results.

10x Science was founded by David Stephen Roberts, Ph.D., Andrew Reiter, and Vishnu Tejus, out of Professor Carolyn Bertozzi's Nobel laureate laboratory at Stanford University. The three founders shared a common frustration: they were studying what happens molecularly when an immune cell meets a cancer cell, one of the most critical problems in cancer research, and the tools they needed to characterize the proteins involved did not exist.

• Roberts, a Damon Runyon Cancer Research Fellow with over 38 publications in the Nature and ACS families of journals, spent his career developing the foundational science of next-generation protein characterization.
• Reiter trained at the Broad Institute of MIT and Harvard, where he built the analytical tools pharma uses to understand how drugs bind their targets, before joining the Bertozzi lab at Stanford as a Ph.D. student.
• Tejus is a two-time Y Combinator founder who went to college at age 11. The three founders share a conviction that the life sciences and the technology world have been working on deeply complementary problems without ever connecting, and 10x Science is the bridge between them.

"The people building AI have historically not been life scientists, and the life scientists have not been building AI; we come from both worlds," says co-founder and CEO David Stephen Roberts. "We realized we could build something that had never existed: an AI system with the scientific depth to reason about proteins the way the best experts do, but at a speed and scale no human team can match. For the first time, we can begin to ask the question that the entire pharmaceutical industry has never been able to answer: across thousands of characterized therapeutics, what molecular patterns distinguish the drugs that work from the ones that do not."

The platform's core capability is deep memory: it learns from every dataset, processing and developing an increasingly deep understanding of each customer's molecular portfolio over time. Every result is explainable and traceable, which is essential in a regulated industry where characterization results appear in filings to the FDA. Legacy tools start from zero with every analysis. Combined with the founding team's unique expertise at the intersection of chemistry, biology, mass spectrometry, and modern AI architecture, the company is positioned to define a new category in the life sciences.

"AI has already made meaningful contributions to biology at the prediction layer, asking what a protein might look like based on its sequence," says co-founder and COO Andrew Reiter. "What no one has built is AI for the characterization layer, where you interpret real experimental data from real therapeutic molecules: that is the layer where drug development decisions are actually made, and it has remained painfully manual."

The company's vision extends well beyond faster protein characterization. As the platform processes more molecules across more organizations, 10x Science is building toward a shared layer of molecular intelligence for the life sciences: a deep, evolving understanding of protein therapeutics grounded in real experimental data at a depth and scale that has never existed.

"This is a critical moment in pharma; the industry is looking for AI that actually works, and protein characterization is needed at every stage of the drug lifecycle regardless of whether any single drug succeeds or fails. We're talking about the infrastructure layer of drug development," says Zoe Perret, partner at Initialized Capital. "The 10x Science founders helped build this field, and they're now showing up with a product that solves an expensive, critically important problem. There is no more credible team to do this."

"Biologics are the fastest-growing segment of the pharmaceutical industry and are the most complex to develop. Every antibody, every cell therapy, every engineered protein requires characterization at a level of detail that existing tools simply weren't designed to handle. The field has outgrown its infrastructure. That's not sustainable," says Carolyn Bertozzi, 2022 Nobel Laureate and Stanford University Professor. "I've spent my career at the intersection of chemistry and biology, trying to understand how molecules behave in living systems. The biggest constraint I see across the field, whether in academic labs or industry, is the gap between the data we can generate and the insights we can extract. 10x Science closes that gap."

Right now, the pharmaceutical industry is sitting on an enormous amount of molecular knowledge that has never been aggregated or learned from at scale. 10x Science's AI can characterize any protein, with implications spanning cancer biology, neurodegeneration, infectious disease, agriculture, and fundamental research into how living systems work. With this funding, 10x Science is hiring Founding Engineers and expanding its work with pharmaceutical and biotech partners to open the doors for these applications.

"If we build this right, we give people across every discipline access to a new paradigm of molecular understanding that has never been possible before," says Roberts. "10x Science can be the foundational layer of molecular intelligence for the life sciences. If we are, the world gets a deeper understanding of the molecules that govern health, disease, and life itself. That understanding belongs to everyone."