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Revert "Update OpenADMET.md" #88

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Jan 17, 2025
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Revert "Update OpenADMET.md" #88

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5 changes: 1 addition & 4 deletions content/programs/projects/OpenADMET.md
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Expand Up @@ -3,17 +3,14 @@ title: "OpenADMET"
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intro: "The OpenADMET Project is developing open tools and datasets to predict and resolve ADMET challenges, reducing drug discovery failure rates and accelerating access of treatments to patients."
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## OpenADMET

OpenADMET is redefining how scientists address ADMET (absorption, distribution, metabolism, excretion, and toxicity) challenges in drug discovery—issues responsible for over 50% of drug development failures. Through an innovative, open-source framework, OpenADMET is investigating the "anti-targets" underlying ADMET-related failures, building predictive AI models and datasets that are accessible to all. The initiative harnesses nanoscale chemistry, high-throughput structural and functional assays, and AI-driven active learning to efficiently explore chemical space and resolve pharmacokinetic and toxicological liabilities early in the drug development pipeline.

In collaboration with academia and industry, OpenADMET applies cutting-edge structural biology methods, such as X-ray crystallography and cryo-EM, to enhance model accuracy and predict how drugs interact with key anti-targets. The project is committed to generating high-quality, FAIR (Findable, Accessible, Interoperable, and Reusable) datasets and open-source tools that integrate seamlessly into modern drug discovery workflows.
Beyond tools and datasets, OpenADMET addresses critical gaps in pharmacogenomics by incorporating genetic diversity into its models, ensuring equitable benefits across populations historically underrepresented in clinical trials. By focusing on universal ADMET challenges rather than specific drug targets, OpenADMET paves the way for safer, more effective therapies while reducing costs and accelerating timelines in drug discovery. With a vision of transforming preclinical optimization, OpenADMET is building a future where ADMET-related failures no longer hinder innovation in medicine.

**Website** <>
**Github** <>
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