Drug discovery

Drug Discovery is One of the Hardest Problems in Science. Large Quantitative Models Were Built to Solve it.

SandboxAQ's Large Quantitative Models (LQMs) combine physics-based simulation with machine learning to accelerate life sciences, drug discovery, and drug development through a proprietary three-layer infrastructure.

Who We Are

SandboxAQ is a science-first technology company spun out of Alphabet in 2022. Our drug discovery team includes a dedicated biopharma core of 70+ specialists. These include over 48 domain PhDs across computational chemistry, medicinal chemistry, computational biology, bioinformatics– who work alongside AI and software engineers specialized in cloud-scale molecular simulation.

Recent Breakthrough Research

SandboxAQ and the OpenFold Consortium Launch AQAffinityOpen-source, Structure-free Binding Affinity Prediction Built on OpenFold

SAIR Dataset for Binding Affinity

Nonequilibrium Chimeric Switching (NEX) Stabilizes Binding Free Energy Calculations Across Chemical Space

On improving experimental binding affinity predictions with synthetic data

How We Work With You

SandboxAQ offers three ways to access and deploy our LQMs

LQM-Enabled LLMs

Connect SandboxAQ's LQMs to your existing chat LLM or cloud environment via our Model Context Protocol (MCP). Run scientific queries through the interface your team already uses—no infrastructure overhaul required.

Enterprise Licensing

Deploy SandboxAQ LQMs within your own operational environment. Fine-tune models on your proprietary data and access dozens of specialized modules — from binding affinity prediction to generative molecule design — on a scalable inference model.

Frontier Partnerships

For organizations pursuing category-defining outcomes, we offer long-term, shared-risk engagements with milestone-based alignment and ongoing commercial milestones. We co-create novel IP alongside your team and we have skin in the game.

What Our Partners Are Saying

“With SandboxAQ’s platform, we increased the chemical exploration space from 250,000 molecules to 5.6 million. We identified candidate molecules faster and more efficiently with a hit rate 30 times greater.”

Dr. Stanley Prusiner,
Nobel Laureate, UCSF

“This undruggable protein target has been by far our toughest drug discovery target to date. Having enabled medicinal chemistry on multiple promising starting points is an enormous achievement and extremely exciting.”

Dr. Klaus Klumpp, Co-Founder and President of Riboscience

“SandboxAQ’s leapfrog technology could significantly impact both preclinical and clinical development of drugs, and we look forward to seeing how it could support us in delivering life-changing treatments to patients worldwide, faster”

Paul Hudson,
former CEO of Sanofi