SandboxAQ brings its drug discovery models to Claude — no PhD in computing required

Source: TechCrunch

Introduction

Drug discovery is one of the most expensive failures in modern industry. Finding a single viable molecule can take a decade and cost billions, and most candidates still don’t make it. A generation of AI startups has promised to fix that — most have made the problem less painful for researchers, who are already technically sophisticated enough to use the tools.

But SandboxAQ thinks 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 — putting powerful drug discovery and materials science tools behind a conversational interface that requires no specialized computing infrastructure to use.

SandboxAQ Overview

Founded roughly five years ago as an Alphabet spin‑out, SandboxAQ counts Eric Schmidt, Google’s former CEO, as its chairman. The company has raised more than $950 million from investors (source) and built a number of business lines, including a cybersecurity business (AqtiveGuard).

Large Quantitative Models (LQMs)

One of the more unique things SandboxAQ does is produce large quantitative models (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 both molecular dynamics and microkinetics—the study of how chemical reactions unfold at the molecular level.

“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.

Integration with Claude

By embedding LQMs into Claude, Anthropic’s conversational AI, SandboxAQ makes frontier quantitative models accessible through natural language. As Nadia Harhen, SandboxAQ’s General Manager of AI Simulation, told TechCrunch:

“For the first time, we have a frontier [quantitative] model on a frontier LLM that someone can access in natural language.”

Previously, users of SandboxAQ’s LQMs would have had to provide their own digital infrastructure to run the models.

Market Context

Other well‑funded bets on better models—such as Chai Discovery (TechCrunch article) and Isomorphic Labs (TechCrunch article)—have focused on the science. SandboxAQ is focused on who can actually use it.

Customer Perspective

SandboxAQ’s customers tend to be computational scientists, research scientists, or experimentalists working 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.