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Related Experiment Video

Updated: Jun 27, 2025

Evaluation of Nanoparticle Uptake in Tumors in Real Time Using Intravital Imaging

Evaluation of Nanoparticle Uptake in Tumors in Real Time Using Intravital Imaging

Published on: June 21, 2011

Tumor-On-A-Chip Models for Predicting In Vivo Nanoparticle Behavior.

Kim E de Roode¹, Khadijeh Hashemi¹, Wouter P R Verdurmen¹

¹Department of Medical BioSciences, Radboud University Medical Center, Geert Grooteplein 28, Nijmegen, 6525 GA, The Netherlands.

Small (Weinheim an Der Bergstrasse, Germany)

|May 3, 2024

Summary

This summary is machine-generated.

Microfluidic tumor-on-a-chip models enhance cancer therapy research by simulating the tumor microenvironment (TME). These advanced in vitro models improve prediction of nanoparticle delivery, though protein corona and phagocytosis require further study.

Keywords:

drug delivery nanoparticles protein corona tumor targeting tumor‐on‐a‐chip

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Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

Area of Science:

Biomedical Engineering
Nanotechnology
Cancer Research

Background:

Nanosized drug formulations are crucial for improving cancer therapy.
Predicting in vivo nanoparticle (NP) behavior is complex due to the tumor microenvironment (TME).
Microfluidic tumor-on-a-chip models offer advanced in vitro testing for NP targeting.

Purpose of the Study:

To review the state-of-the-art microfluidic tumor-on-a-chip models for investigating nanoparticle delivery to solid tumors.
To classify these models based on compartmentalization and cell composition.
To critically evaluate their physiological relevance in simulating the TME.

Main Methods:

Description of the tumor microenvironment (TME).
Classification of microfluidic tumor-on-a-chip models (single/multi-compartment, tumor only/TME).
Critical evaluation of the physiological relevance of existing models.

Main Results:

Microfluidic tumor-on-a-chip models significantly improve TME simulation compared to 2D cultures and static 3D spheroids.
These models enhance the understanding of nanoparticle behavior in a tumor context.
The impact of protein corona and phagocytosis on NP delivery requires further investigation.

Conclusions:

Microfluidic tumor-on-a-chip systems represent a significant advancement for in vitro cancer research.
Further refinement is needed, focusing on understanding the role of protein corona and phagocytosis for enhanced predictive capacity.
These models are vital for advancing nanoparticle-based cancer therapies.