Residential College | false |
Status | 已發表Published |
How can machine learning and multiscale modeling benefit ocular drug development? | |
Wang, Nannan1; Zhang, Yunsen1; Wang, Wei1; Ye, Zhuyifan1; Chen, Hongyu1,2; Hu, Guanghui2; Ouyang, Defang1,3 | |
Source Publication | Advanced Drug Delivery Reviews |
ISSN | 0169-409X |
2023-03-10 | |
Abstract | The eyes possess sophisticated physiological structures, diverse disease targets, limited drug delivery space, distinctive barriers, and complicated biomechanical processes, requiring a more in-depth understanding of the interactions between drug delivery systems and biological systems for ocular formulation development. However, the tiny size of the eyes makes sampling difficult and invasive studies costly and ethically constrained. Developing ocular formulations following conventional trial-and-error formulation and manufacturing process screening procedures is inefficient. Along with the popularity of computational pharmaceutics, non-invasive in silico modeling & simulation offer new opportunities for the paradigm shift of ocular formulation development. The current work first systematically reviews the theoretical underpinnings, advanced applications, and unique advantages of data-driven machine learning and multiscale simulation approaches represented by molecular simulation, mathematical modeling, and pharmacokinetic (PK)/pharmacodynamic (PD) modeling for ocular drug development. Following this, a new computer-driven framework for rational pharmaceutical formulation design is proposed, inspired by the potential of in silico explorations in understanding drug delivery details and facilitating drug formulation design. Lastly, to promote the paradigm shift, integrated in silico methodologies were highlighted, and discussions on data challenges, model practicality, personalized modeling, regulatory science, interdisciplinary collaboration, and talent training were conducted in detail with a view to achieving more efficient objective-oriented pharmaceutical formulation design. |
Keyword | Computational Pharmaceutics In Silico modelIng & Simulation Machine Learning Mathematical Modeling Molecular Modeling Ocular Drug Development Pharmacokinetic/pharmacodynamic Modeling |
Language | 英語English |
DOI | 10.1016/j.addr.2023.114772 |
URL | View the original |
Volume | 196 |
Pages | 114772 |
WOS ID | WOS:000956545900001 |
WOS Subject | Pharmacology & Pharmacy |
WOS Research Area | Pharmacology & Pharmacy |
Indexed By | SCIE |
Scopus ID | 2-s2.0-85150245912 |
Fulltext Access | |
Citation statistics | |
Document Type | Review article |
Collection | DEPARTMENT OF PUBLIC HEALTH AND MEDICINAL ADMINISTRATION Faculty of Science and Technology Institute of Chinese Medical Sciences THE STATE KEY LABORATORY OF QUALITY RESEARCH IN CHINESE MEDICINE (UNIVERSITY OF MACAU) |
Corresponding Author | Ouyang, Defang |
Affiliation | 1.State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China 2.Faculty of Science and Technology (FST), University of Macau, Macau, China 3.Department of Public Health and Medicinal Administration, Faculty of Health Sciences (FHS), University of Macau, Macau, China |
First Author Affilication | Institute of Chinese Medical Sciences |
Corresponding Author Affilication | Institute of Chinese Medical Sciences; Faculty of Health Sciences |
Recommended Citation GB/T 7714 | Wang, Nannan,Zhang, Yunsen,Wang, Wei,et al. How can machine learning and multiscale modeling benefit ocular drug development?[J]. Advanced Drug Delivery Reviews, 2023, 196, 114772. |
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