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Xinglin Lecture Series No. 142 - Pharmacy Chapter:Exploration and Application Research in Artificial Intelligence Drug Design Theory

Author: Date: 2024-09-15

Lecture Title: Exploration and Application Research in Artificial Intelligence Drug Design Theory

Date and Time: September 19, 2024 (Thursday) 15:30-16:30

Venue: Wisdom Classroom 404, Zhizhen Building, Ningbo University Health Science Center

Personal Introduction: Zhu Weiliang

Zhu Weiliang is a researcher at the Shanghai Institute of Materia Medica, Chinese Academy of Sciences. He also serves as a doctoral supervisor, group leader, and director of the Center for Drug Discovery and Design at the Shanghai Institute of Materia Medica.

He has led a series of scientific research tasks including the National Natural Science Foundation, the Tenth Five-Year National Key Technology R&D Program, the Eleventh and Twelfth Five-Year National High-Tech Research and Development (863) Projects, the Twelfth Five-Year National Major New Drug Creation Special Subprojects, the Thirteenth and Fourteenth Five-Year National Key R&D Program Projects, and major basic research projects funded by the Shanghai Science and Technology Commission.

His main research areas include artificial intelligence drug design and innovative drug development, with a special focus on the development of new methods and theories in artificial intelligence drug design. He applies these theoretical methods to the research of innovative drugs for major diseases such as cancer, diabetes, and infectious diseases. Conducting drug design and structural optimization studies targeting disease proteins like those in diabetes, cancer, and infectious diseases, he has discovered a series of drug-active compounds with further development prospects. He integrates computational simulation and data mining methods, combining them with medicinal chemistry and pharmacology techniques, to conduct innovative drug research on traditional Chinese medicines and their active ingredients. He employs high-throughput computational simulation methods to study new uses for old drugs. Three new drug development projects have been patented and realized in industrial transformation, predicting and promoting two investigator-initiated clinical studies for old drugs.

His research group currently includes 3 researchers (including one National Science Fund for Distinguished Young Scholars), 1 associate researcher, 1 senior experimentalist, and 1 research assistant. They have published over 300 papers and submitted more than 80 invention patent and software copyright applications (with 49 granted). They have supervised or co-supervised 60 doctoral and master's students.


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Student

Xinglin Lecture Series No. 142 - Pharmacy Chapter:Exploration and Application Research in Artificial Intelligence Drug Design Theory

Author: Date: 2024-09-15

Lecture Title: Exploration and Application Research in Artificial Intelligence Drug Design Theory

Date and Time: September 19, 2024 (Thursday) 15:30-16:30

Venue: Wisdom Classroom 404, Zhizhen Building, Ningbo University Health Science Center

Personal Introduction: Zhu Weiliang

Zhu Weiliang is a researcher at the Shanghai Institute of Materia Medica, Chinese Academy of Sciences. He also serves as a doctoral supervisor, group leader, and director of the Center for Drug Discovery and Design at the Shanghai Institute of Materia Medica.

He has led a series of scientific research tasks including the National Natural Science Foundation, the Tenth Five-Year National Key Technology R&D Program, the Eleventh and Twelfth Five-Year National High-Tech Research and Development (863) Projects, the Twelfth Five-Year National Major New Drug Creation Special Subprojects, the Thirteenth and Fourteenth Five-Year National Key R&D Program Projects, and major basic research projects funded by the Shanghai Science and Technology Commission.

His main research areas include artificial intelligence drug design and innovative drug development, with a special focus on the development of new methods and theories in artificial intelligence drug design. He applies these theoretical methods to the research of innovative drugs for major diseases such as cancer, diabetes, and infectious diseases. Conducting drug design and structural optimization studies targeting disease proteins like those in diabetes, cancer, and infectious diseases, he has discovered a series of drug-active compounds with further development prospects. He integrates computational simulation and data mining methods, combining them with medicinal chemistry and pharmacology techniques, to conduct innovative drug research on traditional Chinese medicines and their active ingredients. He employs high-throughput computational simulation methods to study new uses for old drugs. Three new drug development projects have been patented and realized in industrial transformation, predicting and promoting two investigator-initiated clinical studies for old drugs.

His research group currently includes 3 researchers (including one National Science Fund for Distinguished Young Scholars), 1 associate researcher, 1 senior experimentalist, and 1 research assistant. They have published over 300 papers and submitted more than 80 invention patent and software copyright applications (with 49 granted). They have supervised or co-supervised 60 doctoral and master's students.