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SettingsResearch demo · not for clinical or commercial use
Corollary
  1. Catalog
  2. Chemistry & ADMET
  3. ADMET-AI

Chemistry & ADMET · Swanson et al., Stanford

ADMET-AI

52 ADMET endpoints in one call — hERG, BBB, CYP, clearance, solubility, Tox21.

Commercial use permittedThe MIT licence allows use in commercial research and products.MIT
Availability
On demand
Typical latency
3.0s
Credits per run
~6
Compute tier
A · Fast

1–30s

Runs on On-demand GPU

Runs on our servers with on-demand compute. A first run needs time to load the model; active capacity can be reused and scales down when idle.

Run this model

ADMET-AI

Canonical SMILES for the small molecule.

Needs ligand smiles

About this model

The breadth is the value: absorption, distribution, metabolism, excretion and toxicity computed together, so you see the whole liability profile at once rather than discovering the hERG problem three months in. Each endpoint is a Chemprop D-MPNN ensemble trained on measured compounds from the Therapeutics Data Commons, and each result is reported next to where the molecule sits against approved drugs — which is the only practical way to read an endpoint you do not use daily. Send a series and you get a ranked comparison.

Standardized I/O contract

Every model in the Hub speaks the same contract, which is what lets the Router and the agent call any of them without special-casing.

Inputs

  • smilessmiles · required

    Ligand SMILES

  • focusselect

    Report

Outputs

  • admettable

    All endpoints with predicted value and interpretation.

Specification

Hardware
1× A100 16GB
GPU memory
CPU only
Version
2.0.1
Licence
MIT
Backend
On demandOn-demand GPU
MCP server
mcp-molecule-server

Tasks

admet

Chains well with

  • Molecular Property CalculatorLipinski, Veber and lead-likeness descriptors computed from SMILES — instantly, free.
  • Boltz-2Structure and binding affinity in one pass, approaching FEP accuracy 1000× faster.
admettoxicityliabilityflagship