HomeSandboxAQ brings drug discovery AI to Claude, no computing PhD needed
Drug discovery remains one of the costliest challenges in modern industry. Identifying a single viable molecule can take a decade and billions of dollars, and most candidates still fail. A wave of AI startups has promised to change that — though most have only made the process slightly easier for researchers who are already technically proficient.
SandboxAQ, however, believes the 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 — making powerful drug discovery and materials science tools accessible through a conversational interface that requires no specialized computing infrastructure.
Founded approximately five years ago as an Alphabet spinout, SandboxAQ counts Eric Schmidt, Google's former CEO, as its chairman. The company has raised over $950 million from investors and has developed several business lines, including cybersecurity.
One of SandboxAQ's more distinctive offerings, however, is its large quantitative models, or LQMs. These proprietary models are "physics-grounded," meaning they are built on the laws of the physical world rather than text patterns. They can perform quantum chemistry calculations and simulate molecular dynamics as well as microkinetics — the study of how chemical reactions unfold at the molecular level. This matters because it allows researchers to predict how candidate molecules will behave before any lab work begins.
"Trained on real-world lab data and scientific equations, LQMs are AI models built for the quantitative economy — a $50+ trillion sector covering biopharma, financial services, energy, and advanced materials," the company stated in a press release, which strongly implies that Sandbox AQ is not building yet another chatbot or code assistant — it is pursuing the economy that AI is meant to transform.
Chai Discovery and Isomorphic Labs — both well-funded bets on better models — have focused on the science. SandboxAQ, however, focuses 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 had to provide their own digital infrastructure to run the models.
SandboxAQ's customers are typically computational scientists, research scientists, or experimentalists. Most work at large pharmaceutical or industrial companies, looking for new materials that can become marketable products.
"Our customers come to us because they've tried all the other software available, and the complexity of their problem is such that it either didn't work or didn't yield positive results when applied in the real world," said Harhen.
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Drug discovery remains one of the costliest challenges in modern industry. Identifying a single viable molecule can take a decade and billions of dollars, and most candidates still fail. A wave of AI startups has promised to change that — though most have only made the process slightly easier for researchers who are already technically proficient.
SandboxAQ, however, believes the 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 — making powerful drug discovery and materials science tools accessible through a conversational interface that requires no specialized computing infrastructure.
Founded approximately five years ago as an Alphabet spinout, SandboxAQ counts Eric Schmidt, Google's former CEO, as its chairman. The company has raised over $950 million from investors and has developed several business lines, including cybersecurity.
One of SandboxAQ's more distinctive offerings, however, is its large quantitative models, or LQMs. These proprietary models are "physics-grounded," meaning they are built on the laws of the physical world rather than text patterns. They can perform quantum chemistry calculations and simulate molecular dynamics as well as microkinetics — the study of how chemical reactions unfold at the molecular level. This matters because it allows researchers to predict how candidate molecules will behave before any lab work begins.
"Trained on real-world lab data and scientific equations, LQMs are AI models built for the quantitative economy — a $50+ trillion sector covering biopharma, financial services, energy, and advanced materials," the company stated in a press release, which strongly implies that Sandbox AQ is not building yet another chatbot or code assistant — it is pursuing the economy that AI is meant to transform.
Chai Discovery and Isomorphic Labs — both well-funded bets on better models — have focused on the science. SandboxAQ, however, focuses 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 had to provide their own digital infrastructure to run the models.
SandboxAQ's customers are typically computational scientists, research scientists, or experimentalists. Most work at large pharmaceutical or industrial companies, looking for new materials that can become marketable products.
"Our customers come to us because they've tried all the other software available, and the complexity of their problem is such that it either didn't work or didn't yield positive results when applied in the real world," said Harhen.
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