20 February 2018 Label-free detection of protein biomolecules secreted from a heart-on-a-chip model for drug cardiotoxicity evaluation
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Abstract
Efficient methods for the accurate analysis of drug toxicities are in urgent demand as failures of newly discovered drug candidates due to toxic side effects have resulted in about 30% of clinical attrition. The high failure rate is partly due to current inadequate models to study drug side effects, i.e., common animal models may fail due to its misrepresentation of human physiology. Therefore, much effort has been allocated in the development of organ-on-a-chip models which offer a variety of human organ models mimicking a multitude of human physiological conditions. However, it is extremely challenging to analyze the transient and long-term response of the organ models to drug treatments during drug toxicity tests, as the proteins secreted from the organ-on-a-chip model are minute due to its volumetric size, and current methods for detecting said biomolecules are not suitable for real-time monitoring. As protein biomolecules are being continuously secreted from the human organ model, fluorescence techniques are practically impossible to achieve real-time fluorescence labeling in the dynamically changing environment, thus making a label-free approach highly desirable for the organ-on-achip applications. In this paper, we report the use of a photonic-crystal biosensor integrated with a microfluidic system for sensitive label-free bioassays of secreted protein biomolecules from a heart-on-the-chip model created with cardiomyocytes derived from human induced pluripotent stem cells.
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Frank DeLuna, Frank DeLuna, Yu Shrike Zhang, Yu Shrike Zhang, Gilbert Bustamante , Gilbert Bustamante , Le Li, Le Li, Matthew Lauderdale, Matthew Lauderdale, Mehmet R. Dokmeci, Mehmet R. Dokmeci, Ali Khademhosseini, Ali Khademhosseini, Jing Yong Ye, Jing Yong Ye, } "Label-free detection of protein biomolecules secreted from a heart-on-a-chip model for drug cardiotoxicity evaluation ", Proc. SPIE 10510, Frontiers in Biological Detection: From Nanosensors to Systems X, 1051003 (20 February 2018); doi: 10.1117/12.2290399; https://doi.org/10.1117/12.2290399
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