Using deep learning-assisted Surface-enhanced Raman spectroscopy (SERS) technology, a research team led by Professor Jun Ki Kim of the Department of Convergence Medicine of Asan Medical Center recently developed a molecular diagnostic platform that can directly amplify nucleic acids. SERS technology drastically increases Raman spectroscopic signals using the surface plasmon resonance effect in metals.

The research team employed primers fixed on the surface of gold nanoparticles to create a new substrate and directly amplify nucleic acids on the SERS surface. A comparison of the SERS signals before and after amplification revealed that Raman signals of directly amplified nucleic acids were detectable without the need to mix metallic substances. Utilizing deep learning technology for data processing and analysis, the detection time was less than 20 minutes, significantly faster than the conventional method, with sensitivity also exceeding 100 times higher. Notably, when this technology was applied to samples from COVID-19 patients, it demonstrated 100% sensitivity and specificity, confirming its potential for use in molecular diagnostics of infectious diseases.

The research findings were recently published in the prestigious academic journal of nanotechnology, 'ACS Nano.'