SandboxAQ Integrates Quantitative AI Models with Anthropic’s Claude

SandboxAQ has integrated its Large Quantitative Models (LQMs) with Anthropic's Claude, announced in a press release. The integration connects large language models with large quantitative models, allowing users to perform advanced scientific computations for drug discovery and materials science using plain language input.

SandboxAQ’s LQMs are trained on laboratory data and physics-based simulations, covering applications in biopharma, energy, and materials research. Through Claude, users can now access these models without coding, enabling faster movement from research questions to validated results.

The first integrated model, AQCat Adsorption Spin, accelerates catalyst discovery by calculating adsorption energies to identify promising candidates before full-scale evaluation. According to SandboxAQ, the model achieves high accuracy at reduced computational cost, benefiting industries such as green hydrogen, sustainable fuels, and plastics recycling.

SandboxAQ plans to extend the integration to drug discovery models, including AQPotency and AQCell. These models will allow researchers to predict drug efficacy and simulate cellular responses, offering pharmaceutical teams faster computational screening and analysis through Claude’s conversational interface.