Drug discovery is famously expensive - finding a single viable molecule can take a decade and cost billions, and most candidates still fail. A generation of AI startups has promised to fix this, and most have made the problem slightly less painful for researchers who already know how to use the tools.
SandboxAQ, however, thinks the real bottleneck isn't the models. It's the interface. The company has teamed up with Anthropic to integrate its scientific AI models directly into Claude, putting powerful drug discovery and materials science tools behind a conversational interface that requires no specialized computing infrastructure to use.
Founded roughly five years ago as an Alphabet spinout, SandboxAQ counts Eric Schmidt, Google's former CEO, as its chairman. The company has raised more than $950 million from investors and built out several business lines, including cybersecurity.
What sets SandboxAQ apart is its large quantitative models, or LQMs. These proprietary models are "physics-grounded," meaning they're built on the rules of the physical world rather than patterns in text. They can run quantum chemistry calculations and simulate molecular dynamics and microkinetics - the study of how chemical reactions unfold at the molecular level. That matters because it tells researchers how candidate molecules are likely to behave before anyone sets foot in a lab.
"Trained on real-world lab data and scientific equations, LQMs are AI models engineered for the quantitative economy, a $50+ trillion sector spanning biopharma, financial services, energy, and advanced materials," the company said in a news release that strongly suggests SandboxAQ isn't building another chatbot or code assistant - it's chasing the economy that AI is supposed to transform.
Chai Discovery and Isomorphic Labs - both well-funded bets on better models - have focused on the science. SandboxAQ is focused on who can actually use it. "For the first time, we have a frontier [quantitative] model on a frontier LLM that someone can access in natural language," Nadia Harhen, SandboxAQ's general manager of AI simulation, told TechCrunch. Previously, users of SandboxAQ's LQMs would have had to provide their own digital infrastructure to run the models.
SandboxAQ's customers tend to be computational scientists, research scientists, or experimentalists at large pharmaceutical or industrial companies searching for new materials that can become marketable products. "Our customers come to us because they've tried all the other software out there, and the complexity of their problem is such that it didn't work or didn't yield positive results for them when that translation went to take place in the real world," said Harhen.