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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
Cancer-on-a-chip systems at the frontier of nanomedicine
Yu Shrike Zhang1, Yi-Nan Zhang2, Weijia Zhang3
1Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA.
Abstract:
Nanomedicine provides a unique opportunity for promoting drug efficacy through enhanced delivery mechanisms. However, its translation into the clinics has been relatively slow compared with the large amount of research occurring in laboratory settings. Given the limitations of conventional cell culture models and preclinical animal models, we discuss the potential utility of recently developed cancer-on-a-chip platforms, which maximally replicate the pathophysiology of the human tumor microenvironments, as alternatives for effective evaluation of nanomedicine. We begin with a brief discussion of nanomedicine, then chart the history of organ-on-a-chip platform development and their recent evolution as tools for modeling different cancers for assessing nanomedicine efficacy, concluding with future perspectives for the field.
Insights
Cancer-on-a-chip platforms offer a promising solution for evaluating nanomedicine efficacy. These advanced models better replicate human tumors than traditional methods, accelerating clinical translation.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Oncology
Background:
- Nanomedicine enhances drug delivery and efficacy but faces slow clinical translation.
- Conventional cell and animal models have limitations in replicating human tumor microenvironments.
- Organ-on-a-chip technology has evolved significantly for disease modeling.
Purpose of the Study:
- To discuss the utility of cancer-on-a-chip platforms for evaluating nanomedicine.
- To highlight the limitations of current preclinical models for nanomedicine assessment.
- To explore the potential of advanced in vitro models in oncology research.
Main Methods:
- Review of nanomedicine principles and challenges.
- Historical overview of organ-on-a-chip development.
- Analysis of cancer-on-a-chip platforms for nanomedicine efficacy testing.
- Discussion of human tumor microenvironment replication.
Main Results:
- Cancer-on-a-chip platforms closely mimic human tumor pathophysiology.
- These platforms provide a more accurate preclinical evaluation of nanomedicine compared to traditional models.
- The technology shows potential for accelerating the development of novel cancer therapies.
Conclusions:
- Cancer-on-a-chip platforms represent a significant advancement for preclinical nanomedicine evaluation.
- They offer a more predictive model for assessing drug efficacy and tumor response.
- Future development of these platforms is crucial for overcoming barriers in nanomedicine translation.
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