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Updated: Oct 16, 2025

Evaluation of Nanoparticle Uptake in Tumors in Real Time Using Intravital Imaging
Published on: June 21, 2011
A HET-CAM based vascularized intestine tumor model as a screening platform for nano-formulated photosensitizers
Linda Elberskirch1, Ronan Le Harzic1, Dietrich Scheglmann2
1Fraunhofer Institute for Biomedical Engineering, Department Bioprocessing & Bioanalytics, Joseph-von-Fraunhofer-Weg 1, 66280 Sulzbach (Germany).
Abstract:
The development of new tumor models for anticancer drug screening is a challenge for preclinical research. Conventional cell-based in vitro models such as 2D monolayer cell cultures or 3D spheroids allow an initial assessment of the efficacy of drugs but they have a limited prediction to the in vivo effectiveness. In contrast, in vivo animal models capture the complexity of systemic distribution, accumulation, and degradation of drugs, but visualization of the individual steps is challenging and extracting quantitative data is usually very difficult. Furthermore, there are a variety of ethical concerns related to animal tests. In accordance with the 3Rs principles of Replacement, Reduction and Refinement, alternative test systems should therefore be developed and applied in preclinical research. The Hen's egg test on chorioallantoic membrane (HET-CAM) model provides the generation of vascularized tumor spheroids and therefore, is an ideal test platform which can be used as an intermediate step between in vitro analysis and preclinical evaluation in vivo. We developed a HET-CAM based intestine tumor model to investigate the accumulation and efficacy of nano-formulated photosensitizers. Irradiation is necessary to activate the phototoxic effect. Due to the good accessibility of the vascularized tumor on the CAM, we have developed a laser irradiation setup to simulate an in vivo endoscopic irradiation. The study presents quantitative as well as qualitative data on the accumulation and efficacy of the nano-formulated photosensitizers in a vascularized intestine tumor model.
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