The frontier labs are racing to merge AI with biology. The tools they're scrambling to build, we already ship. Predict binding to ~1 kcal/mol, triage millions of compounds with physics-based docking, and extract every structure from the patent literature — production-ready, today.
Trusted by 4 of the world's 10 largest pharma, and researchers at MIT, Stanford, Caltech, Yale, the Francis Crick Institute, and 30+ leading universities across 6 continents.
Outcomes first. The underlying capabilities — FEP, docking, structure extraction, ADMET — power every solution. Access them through DO Studio, the Deep Origin API, or Balto AI.
Physics-based free energy on diverse scaffolds, including scaffold hops. Replace months of synthesis-and-test cycles with hours of compute.
Validation: NN potentials free energy → Powered by FEPHigh-throughput docking with automatic pocket detection. Cut HTS and DEL false positives at the source.
Where docking drops the ball → Powered by DO Dock>98% accuracy. 100x faster than redrawing, 12x faster than incumbents. Search, compare, and analyze whole chemical spaces in minutes.
98% accuracy: how we built it → Powered by DO PatentADMET, drug-likeness, and toxicity flags from structure — surface liabilities while you can still design around them.
Physics-informed ML methods → Powered by Balto AICryptic site detection with AI structure prediction when crystallography is unavailable.
Multiscale modeling pipeline → Powered by Pocket FinderPhysics-based ternary complex modeling for PROTACs. Reactivity and selectivity prediction for covalent.
PROTAC protein dynamics → Powered by FEPSearch · structure prep · docking · FEP · ADMET · visualization — in plain English, on managed compute.
Every prompt above maps to a real platform tool. See the three ways your team can access them →
Studio, API, and Balto are three ways into the same underlying capabilities. Use one, use all three — your medicinal chemists, ML engineers, and biologists each get the interface they want.
No command line. No AWS. No silicon moat.
A unified UI for the full discovery stack — FEP, docking, ADMET, structure prep — without scripting or compute orchestration. Designed for medicinal chemists who want SOTA tools without the tooling tax.
Programmatic control over the entire engine.
A Python client that exposes everything the platform runs — pocket detection, docking, FEP, ADMET, structure extraction. Build it into your existing pipelines or scale it across millions of compounds.
Drug discovery in plain English.
A natural-language interface that searches PDB / ChEMBL / UniProt / patents, runs docking, predicts ADMET, and visualizes results — without anyone needing to write code or learn a new UI.
Up to 90% fewer failed experiments — physics + ML applied before synthesis, validated by published science.
Talk to one of our scientists about how the platform fits into your discovery program.
