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X-ORIGINAL-URL:https://www.med.unc.edu/compmed
X-WR-CALDESC:Events for Computational Medicine
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DTSTART;TZID=America/New_York:20240507T110000
DTEND;TZID=America/New_York:20240507T120000
DTSTAMP:20260527T114008
CREATED:20240501T162049Z
LAST-MODIFIED:20240501T162049Z
UID:10000410-1715079600-1715083200@www.med.unc.edu
SUMMARY:Seminar
DESCRIPTION:Guest Speaker: \nDefang Ouyang\, PhD\, Associate Professor\, University of Macau \n  \nTalk title: \nOpportunity and Challenge of Artificial Intelligence (AI) in Drug Delivery \n  \nBio: \nProf. Ouyang has a multidisciplinary background in pharmaceutics & computer modeling\, with experience in academia and industry. He obtained his bachelor’s (2000) and master’s (2005) in pharmaceutics from Shenyang Pharmaceutical University\, China. He completed his PhD in pharmacy at The University of Queensland\, Australia\, in 2010 and progressed directly to his faculty position (Lecturer in Pharmaceutics\, PI) at Aston University (UK). At the end of 2014\, he moved to the University of Macau. \nSince 2011\, he has pioneered the integration of multi-scale modeling\, artificial intelligence and big data techniques in the field of drug delivery – “computational pharmaceutics“. He has published 2 books\, 5 book chapters\, over 100 refereed SCI journal papers\, and over 100 invited talks. He held 11 approved patents\, which had been used in medicinal products. In this research area\, he edited the first book <Computational Pharmaceutics – The Application of Molecular Modeling in Drug Delivery> (John Wiley & Sons Inc.\, 2015). He serves as the associate editor of <Drug Delivery and Translational Research>\, editorial board/scientific advisor of <Asian Journal of Pharmaceutical Sciences>\, <Pharmaceutical Research> and <Journal of Pharmaceutical Sciences>. He established the first artificial intelligence (AI)-based formulation platform (FormulationAI). He successfully trained 6 PhD and 30 master’s students. \nHis research focused on computational pharmaceutics\, including: \n\nArtificial intelligence (AI) of pharmaceutical formulations: to build the database of pharmaceutical formulations and predict pharmaceutical formulations by machine learning approaches;\nMulti-scale modeling in drug delivery: to integrate quantum mechanics (QM)\, molecular dynamics (MD)\, and physiologically based pharmacokinetic (PBPK) modeling into drug delivery systems;\nPharmacoinformatics: big data analysis of pharmaceutical information from the literature\, patent\, clinical trial\, and marketed products.
URL:https://www.med.unc.edu/compmed/event/seminar-4/
LOCATION:Mary Ellen Jones 3116\, 116 Manning Drive\, Chapel Hill\, NC\, 27599\, United States
ATTACH;FMTTYPE=image/jpeg:https://www.med.unc.edu/compmed/wp-content/uploads/sites/852/2024/05/Defang-Ouyang.jpg
ORGANIZER;CN="Victoria Doyle":MAILTO:vdoyle@email.unc.edu
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DTSTART;TZID=America/New_York:20240510T100000
DTEND;TZID=America/New_York:20240510T110000
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CREATED:20240417T194130Z
LAST-MODIFIED:20240417T194156Z
UID:10000408-1715335200-1715338800@www.med.unc.edu
SUMMARY:Research in Progress
DESCRIPTION:Presenter: Matthew Sutcliffe\, Perou Lab \nTalk Title: Prognostic and predictive modeling in diverse mouse models of triple-negative breast cancer
URL:https://www.med.unc.edu/compmed/event/research-in-progress-11/
LOCATION:Mary Ellen Jones 3116\, 116 Manning Drive\, Chapel Hill\, NC\, 27599\, United States
ATTACH;FMTTYPE=image/jpeg:https://www.med.unc.edu/compmed/wp-content/uploads/sites/852/2024/04/Matthew-Sutcliffe.jpg
ORGANIZER;CN="Victoria Doyle":MAILTO:vdoyle@email.unc.edu
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