CHO LAB @ SKKU - Sensor for Diagnostics

Sensor Systems for Smart Diagnostics and Assay

: Artificial Molecular Recognition Design to Accelerate Development Time

There has been a strong drive to find newbiochemical markers sensing technology for faster and simpler diagnostics, which can directly detect target molecules in on-site samples without complicated steps. Even though traditional analytical chemistry including mass spectroscopy or chromatography has a lot of advantages, we could not accelerate development time due to the complicated development and production process and their non-versatility. To accelerate the diagnostic approaches for various unknown diseases, we are developing a rapid and label-free sensor system based on a unique molecular recognition technique. We design tailored 3D interfaces of the fluorescent nanotransducer and fabricate the preemptive sensor library for target biochemical markers.

We are interested in the development timeline and workflow necessary to generate a sensor for biomarker detection, starting from the identification of the new target itself to deployable hardware ready for a screening of the population. If new target molecules begins to circulate, this workflow can generate a 3D nanointerface library and synthesize recognition candidates within a few days. Computational analysis can be used to predict selectivity and sensitivity performance in advance of experimental validation. Then, the optimized nanosensor with selective recognition for the unknown biomolecular target can be interfaced directly to the existing on-site platform. Based on the sensing and diagnosis data, we are constructing the database of sensor libraries onto a variety of viruses or disease markers. In this way, the workflow allows for a potential feedback loop for continual sensor development targeting new, emerging pathogens, leveraging numerical modeling.

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