ReviewInternational journal of nanomedicine2026
How Key in vivo Models Can Advance Anticancer Nanotherapeutics.
Review in International journal of nanomedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Nanomedicine-Based Strategies Targeting Macrophage Polarization in Breast Cancer Bone Metastasis: An Updated Review.Breast cancer (Dove Medical Press) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nanomedicine offers powerful opportunities for targeted drug delivery and cancer therapy, yet clinical translation remains limited by the complex and dynamic interactions of nanoparticles within biological systems. This review integrates current evidence on how nanoparticle size, shape, and surface properties govern cellular uptake and processing, systemic biodistribution, immune interactions, and therapeutic performance across in vitro, ex vivo, and in vivo models. By comparatively analyzing findings across two-dimensional, three-dimensional, xenograft, and immunocompetent tumor models, this review identifies model-dependent determinants of nanoparticle performance that influence translational outcomes. Foundational studies in two-dimensional monolayers established relationships between physicochemical attributes, endocytic pathways, vesicular trafficking, and exocytosis. Three-dimensional spheroids introduce extracellular matrix density and cellular packing constraints that limit nanoparticle movement and alter uptake trends observed in monolayers. In vivo, xenograft models emphasize the influence of vascular permeability and stromal architecture but often overestimate delivery due to exaggerated enhanced permeability and retention effects and the lack of adaptive immunity. Immunocompetent tumor models capture complement activation, opsonization, macrophage-mediated clearance, dynamic protein corona evolution, and cytokine-driven vascular changes. These immune-mediated processes reshape biodistribution patterns and often diminish ligand-mediated targeting benefits. They operate alongside systemic factors such as renal and hepatosplenic filtration, biotransformation, and species-specific differences in vascular structure and immune composition, influencing nanoparticle pharmacokinetics and therapeutic response. Together, these findings underscore that successful nanomedicine design requires integrating material engineering with an understanding of immune surveillance, vascular biology, tumor microenvironment heterogeneity, and whole-body transport dynamics. Future progress will depend on developing nanoparticles that maintain functional stability in immune-intact hosts, minimize premature clearance, and achieve sustained intratumoral delivery. These advances must be supported by predictive, physiologically relevant models that bridge gaps between in vitro results, preclinical outcomes, and clinical translation.
Indexed as
Identifiers
What OpenQuestion holds
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.