ReviewDrug design, development and therapy2025
Harnessing Organoid Platforms for Nanoparticle Drug Development.
Review in Drug design, development and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Nanoparticle-Based delivery of proteasome inhibitors for glioblastoma Therapy: Strategies to overcome Blood-Brain barrier and therapeutic resistance.Biochemical pharmacology · 2026Review
- Natural and Synthetic Compounds, Swords for Glioblastoma Therapy: From Tumor to Its Microenvironment.International journal of molecular sciences · 2026Review
- Stem cell-based tactics in the remodeling and treatment of intestinal diseases.Stem cell research & therapy · 2026Review
- Bio-magnetic nanomedicine for targeted drug delivery of breast cancer: green synthesis, functional design, and translational challenges.Breast cancer research : BCR · 2026Review
- Organoids for disease modeling and treatment: state-of-the-art.Experimental hematology & oncology · 2026Review
- Construction of Vascularized Intestinal Organoids Based on Scaffolds, Hydrogels, and 3D Printing Technologies and Their Applications in Drug Delivery.International journal of nanomedicine · 2026Review
- From 2D cultures to 3D systems: evolving cancer models at the interface of functional precision medicine and theranostics.Theranostics · 2026Review
- An organoid-guided roadmap for precision delivery of epigallocatechin gallate in oral submucous fibrosis.Frontiers in bioengineering and biotechnology · 2026Review
- Deep Tumor Penetration Using Nanoparticle Delivery Systems: Programmed Design Strategies and Emerging Evaluation Platforms.International journal of nanomedicine · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer nanomedicine holds transformative potential, but its clinical translation remains hindered by the lack of preclinical models that accurately mimic human tumor complexity. Conventional approaches often overlook the dynamic tumor microenvironment (TME) and interpatient variability, leading to unreliable predictions of nanodrug behavior. Here, we present tumor organoids as a transformative solution. These three-dimensional cultures retain the original tumor's architecture, molecular profiles, and TME interactions. Through concrete examples spanning pancreatic, breast, and glioblastoma cancers, we showcase how organoids reliably evaluate nanodrug delivery efficiency, therapeutic effects, and safety profiles. In addition, the establishment of large-scale organoid biobanks further facilitates rapid drug screening and tailored treatment strategies, significantly improving preclinical success rates. Therefore, the organoid-driven paradigm not only overcomes long-standing challenges in tumor modeling but also paves a faster, more reliable path toward clinically effective nanotherapies.
Indexed as
Identifiers
What Socratic 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 Socratic graph.