AceGen: Reinforcement Learning Framework For De-Novo Library Generation
Explore chemical space efficiently with AceGen, Acellera’s chemical language model guided by a state-of-the-art reinforcement learning algorithm. With AceGen virtual libraries of chemical compounds can be rapidly generated while optimizing multiple objectives. Tune the model to your target or optimize your lead with decorative mode. Use AceGen to stimulate new ideas and avoid IP issues by exploring novel and chemically-sane areas of chemical space.
Use cases
- Chemical space exploration: Navigate effectively through chemical space using optimization metrics
- Targeted library generation: Produce target-optimized libraries using QSAR models.
- Scaffold decoration: Optimize your hit while preserving its core.
Results
- Library of compounds with metrics (.smi and .csv files)
- Optimization summary report
Newsletter