Towards machine learning for hydrogel drug delivery systems

Cally Owh; Dean Ho; Xian Jun Loh; Kun Xue

doi:10.1016/j.tibtech.2022.09.019

Towards machine learning for hydrogel drug delivery systems

Trends Biotechnol. 2023 Apr;41(4):476-479. doi: 10.1016/j.tibtech.2022.09.019. Epub 2022 Nov 12.

Authors

Cally Owh¹, Dean Ho², Xian Jun Loh³, Kun Xue⁴

Affiliations

¹ Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Singapore; Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Engineering Block 4, Singapore 117583, Singapore.
² Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Engineering Block 4, Singapore 117583, Singapore; The N.1 Institute for Health (N.1), 28 Medical Drive, National University of Singapore (NUS), 116456, Singapore; The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, 28 Medical Drive, National University of Singapore (NUS), 116456, Singapore; The Department of Pharmacology, Yong Loo Lin School of Medicine, 16 Medical Drive, National University of Singapore (NUS), 117600, Singapore. Electronic address: biedh@nus.edu.sg.
³ Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Singapore; Department of Materials Science and Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117575, Singapore; School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, #01-30 General Office, Block N4.1, 639798, Singapore. Electronic address: lohxj@imre.a-star.edu.sg.
⁴ Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Singapore. Electronic address: xuek@imre.a-star.edu.sg.

PMID: 36376126
DOI: 10.1016/j.tibtech.2022.09.019

Abstract

Hydrogel drug delivery system development is complex and laborious, and machine learning (ML) techniques hold great promise in accelerating the process. We highlight recent advances and strategies for data collection and ML, and we discuss the potential for and barriers to the broader use of ML for hydrogel drug delivery systems.

Keywords: artificial intelligence; drug delivery; hydrogel; machine learning.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Artificial Intelligence*
Hydrogels*
Machine Learning

Substances

Hydrogels