導師資訊

University of Macau

UMAC-SKL of Quality Research in Chinese Medicine

https://sklqrcm.um.edu.mo/de-fang-ouyang/

合理設計用於遞送 mRNA 的脂質納米顆粒

Rational design of lipid nanoparticles for mRNA delivery

1007 药学

1008 中药学

Strong motivation and self-learning ability in computational pharmaceutics area

PhD

Prof. Ouyang is the pioneer and recognized leader in the field of artificial intelligence (AI) for drug delivery and computational pharmaceutics. He has authored two books, 10 book chapters, and over 100 peer-reviewed SCI papers, along with more than 150 invited presentations, including US-FDA. He edited the first book in this research domain (1st Edition in 2015 & 2nd edition in 2024). Additionally, he holds 12 patents that have been utilized in marketed medicinal products. Since 2011, he has pioneered the integration of artificial intelligence, big data and multi-scale modeling techniques in the field of drug/gene delivery - "computational pharmaceutics”. He has developed the crucial "Rule of 5" for reliable AI drug delivery models and has published over 30 SCI papers in this pioneering area, ranking first and solidifying his status as a leader in the field. He also established the first global AI-based formulation platform "FormulationAI" (https://formulationai.computpharm.org/), which has attracted numerous major pharmaceutical companies and top academic institutions. Prof. Ouyang serves as an associate editor and on the editorial boards of several SCI journals, such as Drug Delivery and Translational Research, Asian Journal of Pharmaceutical Sciences, Pharmaceutical Research, Journal of Pharmaceutical Sciences, and npj Drug Discovery. Furthermore, he participates as a reviewer for numerous international grants and chairs multiple international conferences. He is the founding chair of the Computational Pharmacy Society (CPhS). He has been recognized as “World’s Top 2% Scientists” from 2020 to 2024.

• Artificial intelligence (AI) for drug delivery: to develop advanced machine learning algorithms for the prediction of pharmaceutical formulations, such as lipid nanoparticle (LNP) for mRNA/siRNA delivery, long-term sustained release microsphere and various solubilization techniques for water insoluble drugs; • Multi-scale modeling in drug formulations: to combine quantum mechanics (QM), molecular dynamics (MD), mathematical modeling and physiologically based pharmacokinetic (PBPK) modeling into drug and gene delivery systems; • Pharmacoinformatics: big data analysis of pharmaceutical information from the literature, patent, clinical trial and marketed products.

12

7

2

“Rational design of lipid nanoparticles for mRNA delivery”, 2024-2027, FDCT Research Grant (0071/2024/RIA1), 1,910,000 MOP, Macau (PI);