UM develops AI platform to support TCM drug discovery for Alzheimer’s disease

MACAU, April 24 - A research team led by Lu Jiahong, deputy director of the Institute of Chinese Medical Sciences (ICMS) at the University of Macau (UM), in collaboration with Hangzhou MindRank AI Technology Co Ltd and Imperial College London in the UK, has developed an AI platform that integrates a million-compound library and multiple predictive modules for the discovery of bioactive ingredients in traditional Chinese medicine (TCM) and natural products. The team used the platform for virtual screening, followed by cross-species experimental validation, to identify small-molecule TCM compounds with therapeutic potential for Alzheimer’s disease (AD). The findings have been published in the top-tier international journal Nature Biomedical Engineering.

TCM and natural products have long been an important source of drug innovation. However, the chemical complexity and vast number of TCM constituents make traditional screening methods time-consuming and labour-intensive, hindering the modernisation of TCM. To overcome this bottleneck, the research team has developed an AI-driven discovery platform for TCM active ingredients. The platform seamlessly integrates the team’s previous research with cutting-edge AI technologies. Leveraging advanced algorithms and computational models, the platform can efficiently identify TCM ingredients with neuroprotective activity, autophagy-modulating properties, as well as favourable blood-brain barrier (BBB) permeability. The platform has undergone two key iterations (the results of the first generation were published in Nature Biomedical Engineering in 2022). The platform’s natural product and TCM compound library has grown to encompass millions of entries, and the speed and accuracy of screening have both been significantly improved. To date, several candidate compounds have already demonstrated promising effects in animal models of the disease and are currently undergoing further development.

The AI platform is now publicly available (https://deepdrugdiscovery.mindrank.ai/). Its aim is to facilitate the elucidation of TCM mechanisms, accelerate the discovery of innovative drugs, and provide technical support and a platform for the modernisation and internationalisation of TCM.

Over 50 million people worldwide suffer from AD. However, the field has long lacked major therapeutic breakthroughs. Drug development targeting traditional AD targets has faced persistent difficulties, and the amyloid-targeting antibody drugs approved in recent years offer only limited cognitive benefits and are associated with notable side effects. Autophagy, a highly conserved cellular ‘waste clearance’ mechanism that degrades and recycles damaged proteins and old organelles, is essential for maintaining neuronal homeostasis. Numerous studies have shown that autophagic dysfunction in the brains of AD patients leads to the accumulation of toxic substances, such as β-amyloid and hyperphosphorylated tau, which exacerbate neurodegeneration. Therefore, restoring or enhancing autophagy is regarded as a highly promising new strategy for treating AD. The candidate TCM small molecules identified in this study can precisely modulate an mTOR-independent autophagic pathway, promoting the clearance of toxic proteins and thereby slowing disease progression. This underscores the clinical relevance of targeting autophagy as a therapeutic approach for AD.

The corresponding authors of this study are Prof Lu and Niu Zhangming, CEO of Hangzhou MindRank AI Technology Co Ltd. Dong Yu and Zhuang Xuxu, postdoctoral fellows at UM, as well as Xiao Xianglu and Yu Wenfan of Hangzhou MindRank AI Technology Co Ltd, are the co-first authors. Other contributors to the research include: Shen Hanming, associate dean of FHS; Wan Jianbo, deputy director of ICMS; Su Huanxing, professor in ICMS; and Yu Hua and Ouyang Defang, associate professors in ICMS. The research was funded by the University of Macau-Dr. Stanley Ho Medical Development Foundation “Set Sail for New Horizons, Create the Future” Grant (Grant No.: SHMDF-OIRFS/2024/002), the General Program of the National Natural Science Foundation of China (Grant No.: 82271455), the Science and Technology Development Fund of the Macao SAR (Grant Nos.: 0040/2024/RIB1, 0002/2025/NRP), and the University of Macau Development Foundation (Grant Nos.: MYRG-GRG2024-00238-ICMS-UMDF, MYRG-GRG2023-00089-ICMS-UMDF). The full article can be accessed at: https://www.nature.com/articles/s41551-026-01667-x.