Engineered multi-domain lipid nanoparticles for targeted delivery
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 biolog...
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| Published in | Chemical Society reviews Vol. 54; no. 12; pp. 5961 - 5994 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Royal Society of Chemistry
16.06.2025
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| Subjects | |
| Online Access | Get full text |
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| Summary: | 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
in vivo
fate (
e.g.
, 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
de novo
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.
This review introduces a four-domain framework to dissect engineered lipid nanoparticles (LNPs) rationally and explores their programmability,
in vivo
behavior, and emerging AI-driven strategies for design, simulation, and clinical translation. |
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| Bibliography: | Yuanyuan Wei is currently a Postdoctoral Scholar in the Neurology Department, at the University of California, Los Angeles (UCLA). Before that, she was a Research Associate in the Department of Biomedical Engineering (BME) at The Chinese University of Hong Kong (CUHK). She received her BEng degree in Precision Instrument from Tsinghua University in 2018. She earned her PhD degree in BME from CUHK in 2023. Her research encompasses computational bioassay, droplet-based microfluidics, and neurodegenerative disease diagnosis. To date, she has published 21 peer-reviewed research papers, including 11 first-author/corresponding author journal (7)/conference (4) papers. Ken-Tye Yong is a Professor in the School of Biomedical Engineering at the University of Sydney and a senior member of the National Academy of Inventors. His multidisciplinary research spans microfluidics, MEMS, nanomedicine, quantum dot engineering, plasmonic biosensors, gene and drug delivery systems, triboelectric nanogenerators, and biophotonics. His work bridges fundamental science and translational biomedical applications, supporting diagnostics and therapeutic innovations. With over 300 publications garnering more than 25 000 citations, Ken-Tye's research has earned prestigious recognitions, including the Bielby Medal and the Rosenhain Medal. Sherwin Ho graduated from the University of California, Berkeley in 2024 with a degree in Neurobiology. Currently, he is a Research Assistant assisting Dr Yuanyuan Wei at Prof. Chao Peng's Lab in Neurology Department, at the University of California, Los Angeles (UCLA). His research interest encompasses microfluidics, neurodegenerative disease diagnosis, AI-based drug design, and micro/nanotechnology. Zhaoyu Liu is currently pursuing a Master's degree in Biomedical Engineering (BME) at Johns Hopkins University (JHU). He received his BEng degree in BME from The Chinese University of Hong Kong (CUHK) in 2023. His research interests include micro/nanotechnology, with a current focus on cleanroom microfabrication and electrophysiological data analysis. Jingxun Chen is a Master's student in Biomedical Engineering at Johns Hopkins University. She received her BEng in Biomedical Engineering from The Chinese University of Hong Kong in 2023. Her research focuses on cleanroom-based microfabrication of self-folding microfluidic devices for selective perfusion and localized morphogenesis. Ho-Pui Ho (Aaron) received his BEng and PhD in Electrical and Electronic Engineering from the University of Nottingham. Currently serving in the Department of Biomedical Engineering, The Chinese University of Hong Kong as Department Chairman and Professor, his academic interests focus on nano-sized semiconductor materials for photonic and sensor applications, optical instrumentation, surface plasmon resonance biosensors, nanopore single molecule analysis, lab-on-a-chip and biophotonics. He has published over 400 peer-reviewed articles, 33 Chinese and 6 US patents. He is a Fellow of SPIE and HKIE. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 |
| ISSN: | 0306-0012 1460-4744 1460-4744 |
| DOI: | 10.1039/d4cs00891j |