SandboxAQ has announced the integration of its Large Quantitative Models (LQMs) with Claude, Anthropic’s frontier AI model, enabling researchers to access advanced scientific computation through natural language prompts.
The integration allows users to combine large language models with quantitative AI models for applications in drug discovery and materials science, removing the need for specialized coding expertise and complex computational workflows.
SandboxAQ stated that the move is designed to accelerate scientific research by making physics-grounded AI models more accessible to broader research and enterprise teams.
SandboxAQ’s LQMs are trained using real-world laboratory data, quantum chemistry calculations, molecular dynamics simulations, and scientific equations.
The company stated that integrating these models with Claude enables researchers to interact with advanced computational systems using plain-English prompts instead of specialized programming workflows.
The integration is intended to help organizations accelerate research processes across sectors including biopharma, energy, advanced materials, and financial services.
Jack D. Hidary, CEO of SandboxAQ, said:
"Now, researchers can access frontier physics-based models directly inside the AI tools they already use, with no additional infrastructure, code or barriers."
Hidary added:
"Our LQMs bring the rigor of first-principles quantum chemistry to a conversational interface, and that changes how fast a user can move from question to answer across chemistry, materials science, and drug development."
As part of the integration, users can now access AQCat Adsorption Spin through Claude.
AQCat focuses on adsorption energy calculations, which measure how strongly molecules bind to catalyst surfaces — a critical step in catalyst discovery and materials development workflows.
According to SandboxAQ, the model provides high-accuracy results while reducing the time and computational costs traditionally associated with catalyst screening processes.
Catalysts play a major role in chemical manufacturing, including applications related to green hydrogen, sustainable aviation fuel, fertilizer production, and plastics recycling.
Partha P. Mukherjee, Ph.D., Professor and Director of the Center for Advances in Resilient Energy Storage (CARES) at Purdue University, said:
"SandboxAQ's integration with Claude removes one of the key barriers between a researcher's scientific intuition and rigorous physics-grounded computation, accelerating discovery across energy materials and beyond."
SandboxAQ also announced plans to bring additional pharmaceutical AI models to Claude through the same conversational interface.
Upcoming models include:
The company stated that these models aim to reduce the complexity and time required for computational drug discovery workflows.
Nadia Harhen, General Manager of AI Simulation at SandboxAQ, said:
"As we bring these capabilities to Claude, users in pharma and biotech will be able to run workflows that previously required weeks of computational setup in hours."
Harhen added:
"Our drug discovery models are built on the same physics-grounded infrastructure that powers AQCat Adsorption Spin today. This means any researcher, regardless of their technical background, can find a faster path from scientific question to answer."
As enterprises continue adopting AI-driven scientific research platforms, integrations between large language models and domain-specific quantitative AI systems are expected to accelerate innovation across life sciences, chemistry, and advanced materials engineering.
SandboxAQ is a B2B company delivering solutions at the intersection of AI and quantum techniques. The company's Large Quantitative Models (LQMs) deliver critical advances in life sciences, financial services, navigation, and other sectors. SandboxAQ is an independent, growth-backed company funded by leading investors and strategic partners including funds and accounts advised by T. Rowe Price Associates, Inc., Google, Alger, IQT, US Innovative Technology Fund, S32, Paladin Capital, BNP Paribas, Eric Schmidt, Breyer Capital, Ray Dalio, Marc Benioff, Thomas Tull, Yann LeCun, and others.
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