基于多模态人工智能数据融合的中药药动学研究进展  

Survey of Pharmacokinetics of Traditional Chinese Medicine Based on Multimodal Artificial Intelligence Data Fusion

作　　者：郭惠婕 周泳杰 许建真 GUO Huijie;ZHOU Yongjie;XU Jianzhen(Information Construction Management Office,China Pharmaceutical University,Nanjing,Jiangsu 211198,China;College of Science,China Pharmaceutical University,Nanjing,Jiangsu 211198,China)

机构地区：[1]中国药科大学信息化建设管理处,江苏南京211198 [2]中国药科大学理学院,江苏南京211198

出　　处：《数据与计算发展前沿(中英文)》2025年第2期149-160,共12页Frontiers of Data & Computing

基　　金：中央高校基本科研业务费专项资金资助项目(2632024RWPY04)。

摘　　要：【目的】中药因其多成分、多靶点的作用机制而呈现出复杂性。人工智能因其卓越的数据处理能力,在中药成分靶标发现和药效研究中展现出巨大潜力,因此备受学术界和产业界的关注。然而,传统的人工智能方法在处理多维度数据时面临整合难题,导致训练过程模态缺失,从而影响药物识别的准确性和效果。【方法】本文探讨了深度学习等人工智能技术在中药药代动力学中的应用,以及多模态数据融合方法的实践手段,并将详细阐述这些方法在药物-靶标、药物-药物以及蛋白-蛋白相互作用中的应用。【结果】本文为中药靶标预测、药物相互作用和定量分析等药动学研究提供了多角度的知识服务。【结论】多模态数据融合方法的应用有望提升中药研究的效率与准确性,推动中药现代化进程,促进其在全球范围内的广泛应用。[Objective]Traditional Chinese medicine is complex because of its multi-component and multi-target mechanisms of action.With its exceptional data processing capabilities,artificial intelligence has demonstrated significant potential in the discovery of targets and efficacy research concerning traditional Chinese medicine ingredients,thereby attracting considerable attention from both academia and industry.However,conventional artificial intelligence methods encounter challenges in integrating multi-dimensional data during the training process,which can lead to the omission of modalities and subsequently impact the accuracy and effectiveness of drug identification.[Methods]This article explores the application of artificial intelligence technologies,particularly deep learning,in the pharmacokinetics of traditional Chinese medicine.It also examines practical methods for multi-modal data fusion and elaborates on the application of these methods in drug-target interactions,drug-drug interactions,and protein-protein interactions.[Results]This article provides multi-angle knowledge services for pharmacokinetic research such as target prediction of traditional Chinese medicine,drug interaction,and quantitative analysis.[Conclusions]The application of multi-modal data fusion methods is expected to improve the efficiency and accuracy of traditional Chinese medicine research,promote the modernization of traditional Chinese medicine,and promote its widespread application around the world.

关 键 词：多模态数据融合 人工智能 中药学 药代动力学 

分 类 号：R285[医药卫生—中药学]