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Mechanistic study of cancer drug delivery: Current techniques, limitations, and future prospects
Abstract
Cancer drug delivery remains a critical challenge with systemic toxicity, poor drug bioavailability, and a lack of effective targeting. Overcoming these barriers is essential for improving treatment efficacy and patient outcomes. This review discusses current drug delivery techniques that reshape cancer therapy by offering precise, controlled-release tailored to tumor-specific features. Innovations in nanotechnology, immunotherapy, and gene therapy enable interventions at molecular and cellular levels. Radiomics and pathomics integrate high-dimensional data to optimize diagnostics and treatment planning. Combination therapy addresses the complexities of tumor heterogeneity by synergizing multiple agents within a single therapeutic framework, while peptide-drug conjugates enhance specificity and potency. Hydrogel-based systems and microneedle arrays offer localized, sustained release, significantly improving therapeutic outcomes. However, clinical translation of these advancements faces significant barriers such as drug resistance, off-target effects, scalability, cost, and ethical concerns. Moreover, regulatory complexities and the economic feasibility of these therapies highlight the need for innovative frameworks to make them accessible globally. Therefore, there is a need for innovation in gene and cell therapy, next-generation drug delivery platforms, and personalized medicine. This review focuses on recent advancements in drug delivery techniques over the past decade, ev…
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“Despite the theoretical advantages of the enhanced permeability and retention (EPR) effect, tumor heterogeneity can significantly impact nanoparticle accumulation and drug delivery efficiency.”
From Advances in green-synthesized magnetic nanoparticles for targeted cancer therapy: mechanisms, applications, and future perspectives (2026) · cites this paper as [102]
In the citing paper
“Variations in tumor vascularization and the microenvironment can hinder the precise targeting of MNPs, leading to suboptimal therapeutic outcomes.”
From Advances in green-synthesized magnetic nanoparticles for targeted cancer therapy: mechanisms, applications, and future perspectives (2026) · cites this paper as [102]
In the citing paper
“Active targeting strategies, such as ligand–receptor interactions, show promise in increasing selectivity, but challenges persist in achieving consistent targeting across different cancer types [102].”
From Advances in green-synthesized magnetic nanoparticles for targeted cancer therapy: mechanisms, applications, and future perspectives (2026) · cites this paper as [102]
In the citing paper
“Moreover, inconsistent targeting performance is another challenge for MNPs in clinical applications.”
From Advances in green-synthesized magnetic nanoparticles for targeted cancer therapy: mechanisms, applications, and future perspectives (2026) · cites this paper as [102]
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El-khawaga, A. M., Youssef, O. I., El-dydamoni, O. A., Ragab, W. M., & Mohammed, R. A. E. (2026) · European Journal of Medical Research · doi:10.1186/s40001-025-03804-9 · Cited by 14
Metadata
- Authors
- Imtiaz, S., Ferdous, U. T., Nizela, A., Hasan, A., Shakoor, A., Zia, A. W., & Uddin, S.
- Venue
- European Journal of Medicinal Chemistry
- Publisher
- Elsevier BV
- Published
- 2025-06
- Volume
- 290
- Pages
- 117535
- ISSN
- 0223-5234
- Cited by
- 119
- References
- 5
- Language
- en
- Licence
- Funders
- King Fahd University of Petroleum & Minerals
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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