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Towards machine learning for hydrogel drug delivery systems.

Cally Owh1, Dean Ho2, Xian Jun Loh3

  • 1Institute 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.

Trends in Biotechnology
|November 14, 2022
PubMed
Summary

Machine learning (ML) can accelerate complex hydrogel drug delivery system development. This review covers data collection, ML strategies, and discusses the potential and challenges for wider ML adoption in this field.

Keywords:
artificial intelligencedrug deliveryhydrogelmachine learning

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Area of Science:

  • Biomaterials Science
  • Drug Delivery Systems
  • Computational Chemistry

Background:

  • Hydrogel drug delivery system development is intricate and time-consuming.
  • Machine learning (ML) offers potential solutions to streamline these processes.
  • Recent advancements highlight ML's role in optimizing hydrogel formulations.

Purpose of the Study:

  • To review recent advances in applying ML to hydrogel drug delivery.
  • To discuss strategies for data collection and ML implementation.
  • To identify the potential and barriers for broader ML adoption in hydrogel development.

Main Methods:

  • Literature review of ML applications in hydrogel drug delivery.
  • Analysis of data collection and ML strategy trends.
  • Discussion of current challenges and future prospects.

Main Results:

  • ML techniques show significant promise in accelerating hydrogel development.
  • Effective data collection and appropriate ML strategies are crucial for success.
  • Several barriers exist, including data standardization and model interpretability.

Conclusions:

  • ML is poised to revolutionize hydrogel drug delivery system design.
  • Overcoming current barriers will facilitate wider ML integration.
  • Future research should focus on robust data generation and advanced ML models.