Dr. Defang Ouyang's research centers on computational pharmaceutics, combining artificial intelligence and multi-scale modeling to enhance drug delivery and pharmaceutical formulations.

Yiyang Wu is a Ph.D. student at the University of Macau, specializing in applying AI techniques to accelerate pharmaceutical research. She currently focuses on AI-driven ionizable lipid design for mRNA lipid nanoparticles.

Dedicated and self-motivated researcher with 10+years with experience of recombinant protein expression in E. coli and optimizing bioprocess. Developed a total of 5 bioproduct formulations and bioprocess protocols. Collaborated on 5+ projects of probiotic development. Contributed to developing the cell machine interface to control bioprocessing and published 14+ article in bioengineering and biopharmaceutical topic.

Dr. Zheng Ying is a Professor at the State Key Laboratory of Chinese Medicine Quality Research, Institute of Chinese Medical Sciences, University of Macau, and Head of the Department of Pharmaceutical Sciences, Faculty of Health Sciences, University of Macau. Her research interests include novel drug delivery systems and their in vivo fate studies, including oral, transdermal and pulmonary delivery of insoluble ingredients; construction of zebrafish models to visualize the in vivo fate of nanomedicines, tumor targeting and immune effects; and machine-learning screening of transdermal enhancers and their experimental validation. She has hosted and participated in the Overseas Research Fund for Overseas Scholars of Natural Science Foundation of Hong Kong, Hong Kong and Macao, Macao Science and Technology Development Fund, and Erasmus Mundus Collaborative Research Program in Europe. She serves as an editorial board member of Pharmaceutical Research and Asian Journal of Pharmaceutical Sciences.

Mr. Nannan Wang received his B.Sc. degree in Pharmacy from Sichuan University in 2018, where he built a solid foundation in pharmaceutics. From July 2018 to August 2020, he worked as a pharmaceutical formulation researcher, gaining valuable hands-on experience in industrial pharmaceutics. In 2022, he earned his M.Phil. degree from the University of Macau and is currently pursuing a Ph.D. at the same institution under the supervision of Dr. Defang Ouyang. His research interests lie in computational pharmaceutics, physical pharmaceutics, and intelligent pharmaceutical manufacturing. By integrating advanced computational approaches such as machine learning and multiscale modeling, Mr. Wang aims to improve development efficiency, reduce costs, and ensure the production of high-quality pharmaceutical products.

Prof. Qi ZHAO obtained his PhD from the Department of Biochemistry at the Chinese University of Hong Kong. He conducted postdoctoral research at the National Cancer Institute (NCI) of the National Institutes of Health (NIH) in the United States and at the Memorial Sloan Kettering Cancer Center. He has served at the Faculty of Health Sciences, University of Macau since 2016. In recent years, he has published over 120 papers in journals such as Nature Communications, Leukemia, Journal of Hematology & Oncology, Cell Reports Medicine, Advanced Sciences, and Clinical Cancer Research. He has received the NIH Federal Technology Transfer Award and the Best Research Award of the university. He has led various research projects (total 17) and numerous industrial collaboration projects (Novo Nordisk, China Resources Pharm). He has filed 20 patents and completed the industrial translation of two antibody drugs. His research mainly focuses on antibody immunotherapy and drug delivery.

Ziyang Sun is a graduate student at the Department of Burns and Plastic Surgery, Nanjing Drum Tower Hospital, Clinical College, Nanjing University of Chinese Medicine. His research focuses on host–microbiome–immune interactions in chronic wound healing, with a particular interest in androgen modulation and precision microbiota-targeted therapies. He has experience in diabetic wound models, microbial sequencing (16S rRNA), immunohistochemistry, and transcriptomic profiling. Ziyang is currently exploring AI-driven methods—such as LASSO, random forest, and SHAP—for identifying predictive microbial signatures that influence healing trajectories. He is also engaged in interdisciplinary work combining endocrinology, bioinformatics, and wound biology. His goal is to uncover novel therapeutic strategies that integrate hormonal regulation and microbiome engineering to improve outcomes in patients with non-healing wounds.