Engineered multi-domain lipid nanoparticles for targeted delivery.

Journal: Chemical Society reviews
Published Date:

Abstract

Engineered lipid nanoparticles (LNPs) represent a breakthrough in targeted drug delivery, enabling precise spatiotemporal control essential to treat complex diseases such as cancer and genetic disorders. However, the complexity of the delivery process-spanning diverse targeting strategies and biological barriers-poses significant challenges to optimizing their design. To address these, this review introduces a multi-domain framework that dissects LNPs into four domains: structure, surface, payload, and environment. Engineering challenges, functional mechanisms, and characterization strategies are analyzed across each domain, along with a discussion of advantages, limitations, and fate (, biodistribution and clearance). The framework also facilitates comparisons with natural exosomes and exploration of alternative administration routes, such as intranasal and intraocular delivery. We highlight current characterization techniques, such as cryo-TEM and multiscale molecular dynamics simulations, as well as the recently emerging artificial intelligence (AI) applications-ranging from LNP structure screening to the prospective use of generative models for design beyond traditional experimental and simulation paradigms. Finally, we examine how engineered LNPs integrate active, passive, endogenous, and stimuli-responsive targeting mechanisms to achieve programmable delivery, potentially surpassing biological sophistication in therapeutic performance.

Authors

  • Zhaoyu Liu
    Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, PR China.
  • Jingxun Chen
    Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, 999077, China. aaron.ho@cuhk.edu.hk.
  • Mingkun Xu
    Department of Precision Instrument, Tsinghua University, Beijing, 100084, China; Center for Brain Inspired Computing Research, Tsinghua University, Beijing, 100084, China; Beijing Innovation Center for Future Chip, Beijing, 100084, China.
  • Sherwin Ho
    Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, California, 90095, USA. yuanyuanwei@mednet.ucla.edu.
  • Yuanyuan Wei
    Institute of Technical Biology & Agriculture Engineering, Hefei Institutes of Physical Science, Chinese Academy of Sciences, HeFei City, AnHui Province, China.
  • Ho-Pui Ho
    Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China. aaron.ho@bme.cuhk.edu.hk.
  • Ken-Tye Yong
    School of Biomedical Engineering, The University of Sydney, Sydney, NSW, 2006, Australia.