Bottom-up design of hydrogels for programmable drug release
Cally Owh1, Valerie Ow2, Qianyu Lin1
1Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore (NUS), 21 Lower Kent Ridge Rd, Singapore 119077, Singapore.
Biomaterials Advances
|September 12, 2022
Summary
Hydrogels offer controlled drug delivery for biomedical uses. This review details how synthesis, formulation, fabrication, and environmental factors can be manipulated to precisely program hydrogel release rates for optimized therapeutic outcomes.
Area of Science:
- Biomaterials Science
- Drug Delivery Systems
- Polymer Chemistry
Background:
- Hydrogels are biocompatible materials mimicking native tissue, making them ideal for drug delivery.
- Controlling drug release kinetics from hydrogels is crucial for effective therapeutic regimens, especially complex ones like combinatorial therapy.
- Understanding tunable parameters for hydrogel design is essential for precise drug release modulation.
Purpose of the Study:
- To review physical models governing hydrogel drug release.
- To comprehensively examine controllable parameters influencing hydrogel release rates.
- To provide examples of programmed hydrogel release for temporal and spatial control.
Main Methods:
- Survey of established physical models for hydrogel drug release.
- Systematic analysis of input parameters across synthesis, formulation, fabrication, and environmental stages.
- Illustration of hydrogel programming through practical examples.
Main Results:
- Identified key physical models applicable to hydrogel release.
- Detailed a range of controllable parameters influencing drug release kinetics.
- Demonstrated successful programming of hydrogels for targeted temporal and spatial release.
Conclusions:
- Hydrogel drug release can be precisely programmed using controllable parameters.
- Future directions include leveraging machine learning for advanced hydrogel design and release control.
- Further research is needed to overcome challenges and fully realize the potential of programmed hydrogel drug delivery.
