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SettingsResearch demo · not for clinical or commercial use
Corollary
  1. Catalog
  2. Chemistry & ADMET
  3. REINVENT 4

Chemistry & ADMET · AstraZeneca

REINVENT 4

RL-guided generative chemistry against a multi-objective scoring function.

Commercial use permittedThe Apache-2.0 licence allows use in commercial research and products.Apache-2.0
Availability
Not runnable yet

No backend is configured for this model.

Typical latency
10min
Credits per run
~3,500
Compute tier
C · Heavy

5–30min

Not runnable yet

This model isn't available to run right now.

Run this model

REINVENT 4

up to 264 credits · ~600s typical

About this model

REINVENT optimises molecules toward a composite objective — potency, selectivity, ADMET, synthesizability — using reinforcement learning over a SMILES generator. The industrial standard for de novo design, open-sourced by AstraZeneca.

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

  • scaffoldsmiles

    Scaffold / seed SMILES

  • objectivetext

    Objective

  • num_moleculesnumber

    Molecules

Outputs

  • moleculestable

    Molecules with objective scores.

Specification

Hardware
2× A100
GPU memory
16 GB
Version
4.0
Licence
Apache-2.0
Backend
not configured
MCP server
mcp-molecule-server

Tasks

molecular generationoptimization
generationrlde-novoapache-2