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Artificial intelligence (AI) and machine learning

• Feb 15th at 13:00 | Speakers: Dr De-Fang Ouyang from the University of Macau, Dr Moe Elbadawi, University College London | Chair:  Bahijja Raimi-Abraham

Abstract

Defang Ouyang, University of Macau, Macau, China.

In recent decades pharmaceutics and drug delivery have become increasingly critical in the pharmaceutical industry due to longer time, higher cost, and less productivity of new molecular entities (NMEs). However, current formulation development still relies on traditional trial-and-error experiments, which are time-consuming, costly, and unpredictable.

With the exponential growth of computing capability and algorithms, in recent ten years, a new discipline named computational pharmaceutics integrates with big data, artificial intelligence, and multi-scale modeling techniques into pharmaceutics, which offered great potential to shift the paradigm of drug delivery. Computational pharmaceutics can provide multi-scale lenses to pharmaceutical scientists, revealing physical, chemical, mathematical, and data-driven details ranging across pre-formulation studies, formulation screening, in vivo prediction in the human body, and precision medicine in the clinic. Several formulation cases in the area will be discussed, such as solid dispersion, microsphere and mRNA lipid nanoparticle.

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Prof. Defang Ouyang

Associate professor

Institute of Chinese Medical Sciences/Faculty of Health Sciences,

University of Macau, N22 Avenida da Universidade, Taipa, Macau

Tel: +853-8822-4514

Email: defangouyang@um.edu.mo

Prof. Ouyang has the multidisciplinary background in pharmaceutics & computer modelling, with experience in academia and industry. He obtained his bachelor (2000) and master (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). From the end of 2014, he moved to the University of Macau.

His research focused on computational pharmaceutics, including:

  • Artificial intelligence (AI) of pharmaceutical formulations: to build the database of pharmaceutical formulations and predict pharmaceutical formulations by machine learning approaches;
  • Multi-scale modeling in drug delivery: to integrate quantum mechanics (QM), molecular dynamics (MD) and physiologically based pharmacokinetic (PBPK) modeling into drug delivery systems;
  • Pharmacoinformatics: big data analysis of pharmaceutical information from the literature, patent, clinical trial and marketed products.

Moe Elbadawi, Postdoctoral Fellow 

Moe is a postdoctoral Fellow between UCL and University of Cambridge, specialising in Digital Technologies for improved healthcare. His main research topic is in 3D printing devices for hard-to-treat cancers, with research speciality in AI, and both polymeric and ceramic manufacturing.