Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling

Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model links the concentration-time profile of a drug with its therapeutic effects based on the underlying biological or physiological processes. Clinical endpoints play a pivotal role in drug development. Despite the substantial time and effo...

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Bibliographic Details
Main Authors: Keheng Wu, Xue Li, Zhou Zhou, Youni Zhao, Mei Su, Zhuo Cheng, Xinyi Wu, Zhijun Huang, Xiong Jin, Jingxi Li, Mengjun Zhang, Jack Liu, Bo Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Pharmacology
Subjects:
artificial intelligence (AI)
machine learning (ML)
early drug discovery
PBPK modeling
PD modeling
P-CABs
Online Access:https://www.frontiersin.org/articles/10.3389/fphar.2024.1330855/full

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https://www.frontiersin.org/articles/10.3389/fphar.2024.1330855/full

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