ReviewCellular and molecular bioengineering2025
Engineered Extracellular Vesicles for Targeted Paclitaxel Delivery in Cancer Therapy: Advances, Challenges, and Prospects.
Review in Cellular and molecular bioengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Recent Advances on Extracellular Vesicles: A Natural Nanomaterial for Biomedical Application.Biomimetics (Basel, Switzerland) · 2026Review
- Extracellular Vesicles from the Probiotic YeastNutrients · 2026Article
- Red Blood Cell-Derived Extracellular Vesicles for Gene and RNA Therapeutics: Biological, Engineering, and Translational Challenges.International journal of nanomedicine · 2026Review
- Lysosome as a Chemical Reactor.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Scope: Extracellular vesicles (EVs) have emerged as promising cell-free delivery vehicles for cancer therapy due to their inherent biocompatibility, low immunogenicity, and natural targeting capabilities. EVs derived from various cellular sources offer distinct advantages in drug-loading capacity and therapeutic effectiveness. However, their clinical application is limited by challenges such as poor cargo stability, potential immunogenicity, and off-target effects. These limitations necessitate further surface functionalization of EVs to optimize vesicle stability, targeting precision, and safety of pharmacological cargos. Paclitaxel (PTX), a first-line chemotherapeutic agent effective against multiple cancers, is limited by poor solubility and significant systemic toxicity, highlighting the need for targeted delivery systems. Methods: A literature search was conducted to identify relevant articles published between 1993 and 2025. This review provides a comprehensive overview of EV biogenesis and cellular origins, highlighting recent advances in engineering strategies for PTX delivery. Current progress in employing engineered EVs for PTX delivery in both in vitro and in vivo cancer models, along with practical challenges and future directions in the clinical translation of EV-based PTX delivery, are discussed. Results: Preclinical studies demonstrate that engineered EVs can effectively encapsulate and deliver PTX to tumor sites, improving therapeutic outcomes while minimizing systemic side effects. Despite these advances, challenges remain in optimizing EV isolation, surface modification, PTX loading efficiency, and precise recognition of tumor cells. Conclusion: Engineered EVs represent a promising platform for PTX delivery, combining targeted therapeutic potential with reduced systemic toxicity. Continued research to address technical and translational barriers will be critical for advancing EV-based PTX therapies toward clinical application. Graphical Abstract:
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.