Clinical attrition is about 30% from failure of drug candidates due to toxic side effects, increasing the drug development costs significantly and slowing down the drug discovery process. This partly originates from the fact that the animal models do not accurately represent human physiology. Hence there is a clear unmet need for developing drug toxicity assays using human-based models that are complementary to traditional animal models before starting expensive clinical trials. Organ-on-a-chip techniques developed in recent years have generated a variety of human organ models mimicking different human physiological conditions. However, it is extremely challenging to monitor the transient and long-term response of the organ models to drug treatments during drug toxicity tests. First, when an organ-on-a-chip model interacts with drugs, a certain amount of protein molecules may be released into the medium due to certain drug effects, but the amount of the protein molecules is limited, since the organ tissue grown inside microfluidic bioreactors have minimum volume. Second, traditional fluorescence techniques cannot be utilized for real-time monitoring of the concentration of the protein molecules, because the protein molecules are continuously secreted from the tissue and it is practically impossible to achieve fluorescence labeling in the dynamically changing environment. Therefore, direct measurements of the secreted protein molecules with a label-free approach is strongly desired for organs-on-a-chip applications. In this paper, we report the development of a photonic crystal-based biosensor for label-free assays of secreted protein molecules from a liver-on-a-chip model. Ultrahigh detection sensitivity and specificity have been demonstrated.
Andres W. Morales, Yu Shrike Zhang, Julio Aleman, Parissa Alerasool, Mehmet Remzi Dokmeci, Ali Khademhosseini, and Jing Yong Ye, "Label-free detection of protein molecules secreted from an organ-on-a-chip model for drug toxicity assays," Proc. SPIE 9725, Frontiers in Biological Detection: From Nanosensors to Systems VIII, 972508 (Presented at SPIE BiOS: February 15, 2016; Published: 22 April 2016); https://doi.org/10.1117/12.2212971.
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