Cell-derived nanovesicle-mediated drug delivery to the brain: Principles and strategies for vesicle engineering
Open accessAbstract
Developing strategies toward safe and effective drug delivery into the central nervous system (CNS) with improved targeting abilities and reduced off-target effects is crucial. CNS-targeted drug carriers made of synthetic molecules raise concerns about their biodegradation, clearance, immune responses, and neurotoxicity. Cell-derived nanovesicles (CDNs) have recently been applied in CNS-targeted drug delivery, because of their intrinsic stability, biocompatibility, inherent homing capability, and the ability to penetrate through biological barriers, including the blood-brain barrier. Among these CDNs, extracellular vesicles and exosomes are the most studied because their surface can be engineered and modified to cater to brain targeting. In this review, we focus on the application of CDNs in brain-targeted drug delivery to treat neurological diseases. We cover recently developed methods of exosome derivation and engineering, including exosome-like particles, hybrid exosomes, exosome-associated adeno-associated viruses, and envelope protein nanocages. Finally, we discuss the limitations and project the future development of the CDN-based brain-targeted delivery systems, and conclude that engineered CDNs hold great potential in the treatment of neurological diseases.
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Engineered exosomes carrying RVG-Lamp2b can efficiently cross the blood-brain barrier and deliver catalase mRNA, resulting in a reduction of 6-OHDA-mediated neuroinflammation in a mouse model of Parkinson's disease.
“The designed exosome carrying RVG-Lamp2b was able to efficiently cross the blood–brain barrier (BBB) and deliver the catalase mRNA, resulting in a reduction of 6-OHDA-mediated neuroinflammation in a mouse model of Parkinson’s disease [101, 103].”
From Exosome for mRNA delivery: Strategies and therapeutic applications (2024) · cites this paper as [103]
Two main approaches can be used to enhance targeting ability of exosomes: direct chemical modification or indirect genetic engineering.
“Two main approaches can be used to enhance the targeting ability of exosomes for specific applications: direct modification of exosomes by chemical means or, indirect manipulation of the donor cells through genetic engineering techniques [89, 103, 118–120]”
From Exosome for mRNA delivery: Strategies and therapeutic applications (2024) · cites this paper as [103]
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- Authors
- Liang, Y., Iqbal, Z., Lu, J., Wang, J., Zhang, H., Chen, X., Duan, L., & Xia, J.
- Affiliations
- Shenzhen University (CN)
- Shenzhen KangNing Hospital (CN)
- State Key Laboratory of Digital Medical Engineering (CN)
- Chinese University of Hong Kong (HK)
- Corresponding author
- Duan, Li
- Xia, Jiang
- Venue
- Molecular Therapy
- Publisher
- Elsevier BV
- Published
- 2023-05
- Volume
- 31
- Issue
- 5
- Pages
- 1207-1224
- ISSN
- 1525-0016 (ISSN-L)
- PMC
- PMC10188644
- OpenAlex
- W4306393265
- Cited by
- 162
- References
- 146
- Citations by year
- 2026: 31 · 2025: 54 · 2024: 44 · 2023: 33
- FWCI
- 3.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Molecular Therapy (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- Innovation and Technology Commission
- Shenzhen Science and Technology Innovation Committee
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Life Sciences › Neuroscience › Neurology › Barrier Structure and Function Studies
- Keywords
- brain drug delivery, extracellular vesicles, exosomes, exosome engineering, blood-brain barrier, neurological disorders
- MeSH terms
- Extracellular Vesicles, Blood-Brain Barrier, Brain, Drug Delivery Systems, Exosomes
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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