Research progress of artificial intelligence combined with physiologically based pharmacokinetic models
10.16438/j.0513-4870.2024-0195
- VernacularTitle:人工智能结合生理药代动力学模型的研究进展
- Author:
Long-jie LI
1
;
Pei-ying JI
2
;
Ao-le ZHENG
1
;
Muyesaier ALIFU
1
;
Xiao-qiang XIANG
1
Author Information
1. School of Pharmacy, Fudan University, Shanghai 200120, China
2. Kong Jiang Hospital of Yangpu District, Shanghai 200000, China
- Publication Type:Research Article
- Keywords:
physiologically based pharmacokinetic model;
artificial intelligence;
machine learning;
pharmacokinetics;
pharmaceutical toxicology;
rug-drug interaction
- From:
Acta Pharmaceutica Sinica
2024;59(9):2491-2498
- CountryChina
- Language:Chinese
-
Abstract:
Physiologically based pharmacokinetic (PBPK) models have been widely used to predict various stages of drug absorption, distribution, metabolism and excretion. Models based on machine learning (ML) and artificial intelligence (AI) can provide better ideas for the construction of PBPK models, which can accelerate the prediction speed and improve the prediction quality of PBPK. ML and AL can complement the advantages of PBPK model to accelerate the progress of drug research and development. This review introduces the application of machine learning and artificial intelligence in pharmacokinetics, summarizes the research progress of physiological pharmacokinetic models based on machine learning and artificial intelligence, and analyzes the limitations of machine learning and artificial intelligence applications and their application prospects and prospects.
