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Swanson2023 - ADMET-AI: To evaluate the pharmacokinetics property of large-scale chemical libraries

ABSTRACT: A framework based on ensemble of five Chemprop-RDKit models, for fast batch prediction of ADMET properties of small molecules. Model Type: Predictive machine learning model. Model Relevance: Fast batch prediction for ADMET properties Model Encoded by: Dhanshree (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos7d58

SUBMITTER: Zainab Ashimiyu-Abdusalam

PROVIDER: MODEL2408070002 | BioModels | 2024-08-07

REPOSITORIES: BioModels

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ADMET-AI: A machine learning ADMET platform for evaluation of large-scale chemical libraries.

Swanson Kyle K Walther Parker P Leitz Jeremy J Mukherjee Souhrid S Wu Joseph C JC Shivnaraine Rabindra V RV Zou James J

bioRxiv : the preprint server for biology 20231228

<h4>Summary</h4>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). We developed ADMET-AI, a machine learning platform that provi ...[more]

PMID: 38234753

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