Garg, S., Singla, P., Kaur, S. et al. (7 more authors) (2025) Future Perspectives on the Automation and Biocompatibility of Molecularly Imprinted Polymers for Healthcare Applications. Macromolecules, 58 (3). pp. 1157-1168. ISSN 0024-9297
Abstract
Molecular recognition is of crucial importance in several healthcare applications, such as sensing, drug delivery, and therapeutics. Molecularly imprinted polymers (MIPs) present an interesting alternative to biological receptors (e.g., antibodies, enzymes) for this purpose since synthetic receptors overcome the limited robustness, flexibility, high-cost, and potential for inhibition that comes with natural recognition elements. However, off the shelf MIP products remain limited, which is likely due to the lack of a scalable production approach that can manufacture these materials in high yields and narrow and defined size distributions to have full control over their properties. In this Perspective, we will confer how breakthroughs in the automation of MIP design, manufacturing, and evaluation of performance will accelerate the (commercial) implementation of MIPs in healthcare technology. In addition, we will discuss how prediction of the in vivo behavior of MIPs with animal-free technologies (e.g., 3D tissue models) will be critical to assess their clinical potential.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 May 2025 15:55 |
Last Modified: | 29 May 2025 15:55 |
Status: | Published |
Publisher: | American Chemical Society |
Identification Number: | 10.1021/acs.macromol.4c01621 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:227091 |