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Abstract
Motivation
The emergence of large chemical repositories and combinatorial chemical spaces, coupled with high-throughput docking and generative AI, have greatly expanded the chemical diversity of small molecules for drug discovery. Selecting compounds for experimental validation requires filtering these molecules based on favourable druglike properties, such as Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET).
Results
We developed ADMET-AI, a machine learning platform that provides fast and accurate ADMET predictions both as a website and as a Python package. ADMET-AI has the highest average rank on the TDC ADMET Leaderboard, and it is currently the fastest web-based ADMET predictor, with a 45% reduction in time compared to the next fastest public ADMET web server. ADMET-AI can also be run locally with predictions for one million molecules taking just 3.1 h.
Availability and implementation
The ADMET-AI platform is freely available both as a web server at admet.ai.greenstonebio.com and as an open-source Python package for local batch prediction at github.com/swansonk14/admet_ai (also archived on Zenodo at doi.org/10.5281/zenodo.10372930). All data and models are archived on Zenodo at doi.org/10.5281/zenodo.10372418.
Academic Publication ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries
Research Abstract & Technology Focus
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Frequently Asked Questions (FAQ)
Curated market intelligence mapped to this research.
What is the core focus of the research titled 'ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries'?
This literature focuses on: Abstract Motivation The emergence of large chemical repositories and combinatorial chemical spaces, coupled with high-throughput docking and generative AI, have greatly expanded the chemic...
Are there open-source GitHub repositories related to ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries?
Yes, open-source projects like THU-MAIC/OpenMAIC (Open Multi-Agent Interactive Classroom — Get an immersive, multi-agent learning experience in just one click) are actively building upon these concepts.
Which startups are commercializing the technology behind ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries?
Products like Superset are bringing this to market. Their focus is: Run an army of Claude Code, Codex, etc. on your machine.
What other academic literature is closely related to 'ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries'?
Yes, highly correlated activity was mapped. An entry titled 'ADMET-AI: a machine learning ADMET platform for evaluation of large-scale chemical libraries' discusses this: Abstract Motivation The emergence of large chemical repositories and combinatorial chemi...
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Commercial Realization
Startups and Open Source tools heavily associated with the concepts explored in this paper.
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GitHubTHU-MAIC/OpenMAIC
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GitHubQuipNetwork/xq-rs
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Product HuntSuperset
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Product HuntPadel Chess