Professor Aiping Lyu

About

A renowned expert and academic in the integrative medicine field, Professor Lyu Aiping has been Head & Spokesperson of the China Delegation, International Organization for Standardization Technical Committee on traditional Chinese medicine (ISO/TC249) since 2009.  Besides, he currently serves as President of Good Practice at the Traditional Chinese Medicine Research Association and is a Member of Chinese Pharmacopoeia. He is also Director of the Chinese Medicine Standardization Office in State Administration of Traditional Chinese Medicine (SATCM), and Director of the Chinese Medicine Standard Research Center at the China Academy of Chinese Medical Sciences.

Professor Lyu has published more than 30 books and over 500 articles, including 350 articles in SCI journals such as Nature Medicine, Nature Communication, Biomaterials, Briefings in Bioinformatics and Journal of Proteomic Research. Under his leadership, three standards related to Chinese medicine have been issued. Over the years, he has obtained more than 60 patents from his research activities. 

Professor Lyu is active in integrative medicine research, with a particular focus on clinical evaluation with randomised clinical trials on Chinese medicine pattern classification, pharmacology combining with bio-chemo-informatics analysis on Chinese medicine intervention, and rheumatoid arthritis and cancer drug discovery and development based on Chinese medicine.

Achievements

 Awards

Current Research Work

Being active in integrative medicine research, with particular focus on clinical evaluation with randomized clinical trial with Chinese medicine pattern classification, pharmacology combining with bio-chemo-informatics analysis on Chinese medicine intervention, and rheumatoid arthritis and cancer drug discovery and development based on Chinese medicine.

Chinese medicine pattern classification and clinical trial 

• Pattern classification, the core theory in Chinese medicine clinical practice, is a complementary method to classify individual’s status and contribute to personalized precision medicine. The fundamentals of Chinese medicine in a specific disease in biomedical sciences are the key issue to help scientists understand Chinese medicine. There are at least two Chinese medicine patterns, called hot and cold pattern, in rheumatoid arthritis and those biomedical fundamentals were clarified by using omics data and bioinformatics approaches. The pattern classification in rheumatoid arthritis was shown to be correlated with clinical efficacy in the clinical trials. In Chinese medicine, the same pattern can be classified in different diseases, and the similarities among rheumatoid arthritis, diabetes and coronary heart disease were explored. Further, molecular pattern classification can lead to the development of combination therapeutics and combination drug discovery. (Figure 1)

Combination drug discovery from Chinese herbal formula

• Chinese medicine herbal formula is one of the most important characteristics of Chinese medicine. Compared with western medicine, herbal formula has complex components, unclear targets and mechanisms. It is still a great challenge to clarify the action mechanism of herbal formula under the background of modern biomedicine. In recent years, with the rise of the concept of multi-target drug discovery and the in-depth study of network biology, network pharmacology, as a new scientific concept and research model, is gradually being applied to the study of herbal formula, which is becoming a new interdisciplinary research direction. The emergence of advanced technologies such as omics, informatics and other technological supports benefit for decoding key points of diseases and given highlight on development of better combination drugs models from herbal formula, the effect model can be achieved by combining advanced technologies. (Figure 2)

Data science in Chinese medicines

• Long history of Chinese medicine leave us more data, such as literatures, case studies in herbal formula, Chinese medicine pattern, symptoms, tongue appearance and pulse feelings, etc.. Current technologies produce much more data, such as omics data, chemical data. Those data have been used for integrative medicine study, with the approaches of bioinformatics, chemoinformatics and systems pharmacology, to decipher the molecular mechanism of Chinese medicine pattern in diseases, transformation of the pattern in disease progression with dynamic analysis, and mode of actions of herbal medicines. Some data analysis platforms have been built up, including herbal formula related mechanism exploration, chemical-chemical interactions, herb-chemical drug interactions, optimization of herbal formula, ADME, safety assessment and combination drug discovery mentioned above. The bridge systems between Chinese medicine data in Chinese and biomedical science data in English is being explored. (Figure 3)

Aptamer-based drug discovery and translation medicine

• Aptamers are short single-stranded DNA or RNA oligonucleotides (usually 20–80 nucleotides) that can fold into unique three-dimensional conformations. Aptamers bind to their cognate targets with high-specificity and -affinity through conformational recognition, with dissociation constants (Kd) usually ranging from pico- to nanomolar. Thus, aptamers are also referred to as “chemical antibodies” and are functionally used as antagonists, agonists, or targeting ligands. Due to these characteristics, aptamers are promising agents in both diagnostic and therapeutic applications. Despite great promise and significant efforts in aptamer development over the past 20 years, it is troublesome that only one aptamer has been approved for use in the market. To facilitate the aptamer-based drug discover and translational medicine, we have been focusing on the aptamer selection optimization for high-throughput automatic aptamer screening, aptamer molecular insight for 3D structure determination of aptamer-target complex, diagnostic aptamers for early-stage cancer screening, and therapeutic aptamer-drug conjugates for cancer therapy. This work is granted by Theme-based Research Scheme. (Figure 3)

Research Outputs

Ten Most Representative Publications

• Liang C, Li J, Lu C, Xie D, Liu J, Zhong C, Wu X, Dai R, Zhang H, Guan D, Guo B, He B, Li F, He X, Zhang W, Zhang BT*, Zhang G*, Lu A*. HIF1α inhibition facilitates Leflunomide-AHR-CRP signaling to attenuate bone erosion in CRP-aberrant rheumatoid arthritis. Nat Commun. 2019 Oct 8;10(1):4579.doi: 10.1038/s41467-019-12163-z.
• Liang C, Peng S, Li J, Lu J, Guan D, Jiang F, Lu C, Li F, He X, Zhu H, Au DWT, Yang D, Zhang BT*, Lu A*, Zhang G*. Inhibition of osteoblastic Smurf1 promotes bone formation in mouse models of distinctive age-related osteoporosis. Nat Commun. 2018 Aug 24;9(1):3428. doi: 10.1038/s41467-018-05974-z.
• Li F, Lu J, Liu J, Liang C, Wang M, Wang L, Li D, Yao H, Zhang Q, Wen J, Zhang ZK, Li J, Lv Q, He X, Guo B, Guan D, Yu Y, Dang L, Wu X, Li Y, Chen G, Jiang F, Sun S, Zhang BT*, Lu A*, Zhang G*. A water-soluble nucleolin aptamer-paclitaxel conjugate for tumor-specific targeting in ovarian cancer. Nat Commun. 2017 Nov 9;8(1):1390. doi: 10.1038/s41467-017-01565-6.
• Li D, Liu J, Guo B, Liang C, Dang L, Lu C, He X, Cheung HY, Xu L, Lu C, He B, Liu B, Shaikh AB, Li F, Wang L, Yang Z, Au DW, Peng S, Zhang Z, Zhang BT, Pan X, Qian A, Shang P, Xiao L, Jiang B, Wong CK, Xu J, Bian Z, Liang Z, Guo DA, Zhu H, Tan W, Lu A*, Zhang G*. Osteoclast-derived exosomal miR-214-3p inhibits osteoblastic bone formation. Nat Commun. 2016 Mar 7;7:10872. doi: 10.1038/ncomms10872.
• Liang C, Guo B, Wu H, Shao N, Li D, Liu J, Dang L, Wang C, Li H, Li S, Lau WK, Cao Y, Yang Z, Lu C, He X, Au DW, Pan X, Zhang BT, Lu C, Zhang H, Yue K, Qian A, Shang P, Xu J, Xiao L, Bian Z, Tan W, Liang Z, He F, Zhang L*, Lu A*, Zhang G*. Aptamer-functionalized lipid nanoparticles targeting osteoblasts as a novel RNA interference-based bone anabolic strategy. Nat Med. 2015 Mar;21(3):288-94. doi: 10.1038/nm.3791.