Drug discovery stands as one of the most costly sectors for failure in modern industry. Identifying a single viable molecule often requires a decade and billions of dollars, yet most candidates still fail. While a generation of AI startups has promised to fix that, most existing tools remain accessible only to researchers who are already technically sophisticated enough to use them.
SandboxAQ, an Alphabet spinout, believes the bottleneck isn't the models themselves, but 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 with former Google CEO Eric Schmidt as chairman, SandboxAQ has raised more than $950 million. While the firm has multiple business lines, its most unique offering is Large Quantitative Models (LQMs). These proprietary models are “physics-grounded,” meaning they are built on the laws of physics rather than patterns in text. They can run quantum chemistry calculations and simulate both molecular dynamics and microkinetics—the study of how chemical reactions unfold at the molecular level—allowing researchers to predict molecular behavior before stepping into 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 stated. This suggests SandboxAQ is chasing the fundamental economy that AI is expected to transform, rather than just building another chatbot.
While competitors like Chai Discovery and Isomorphic Labs focus on the science of models, SandboxAQ focuses on accessibility. “For the first time, we have a frontier quantitative model on a frontier LLM that someone can access in natural language,” said Nadia Harhen, SandboxAQ’s GM of AI simulation. Previously, users of these LQMs would have had to provide their own digital infrastructure to run the models.
SandboxAQ’s customers are typically computational and research scientists at large pharmaceutical or industrial companies. Harhen noted that customers often turn to SandboxAQ after other software fails to yield positive results when translating digital discovery into real-world applications.
