Absorption Distribution Metabolism Excretion and Toxicity Property Prediction Utilizing a Pre-Trained Natural Language Processing Model and Its Applications in Early-Stage Drug Development

Absorption Distribution Metabolism Excretion and Toxicity Property Prediction Utilizing a Pre-Trained Natural Language Processing Model and Its Applications in Early-Stage Drug Development

Machine learning techniques are extensively employed in drug discovery, with a significant focus on developing QSAR models that interpret the structural information of potential drugs. In this study, the pre-trained natural language processing (NLP) model, ChemBERTa, was utilized in the drug discove...

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Bibliographic Details
Main Authors: Woojin Jung, Sungwoo Goo, Taewook Hwang, Hyunjung Lee, Young-Kuk Kim, Jung-woo Chae, Hwi-yeol Yun, Sangkeun Jung
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Pharmaceuticals
Subjects:
machine learning
ADMET
drug discovery
in silico screening
Online Access:https://www.mdpi.com/1424-8247/17/3/382

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https://www.mdpi.com/1424-8247/17/3/382

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