Dr. Minji Kang is a postdoctoral researcher at the Korean Institute of Tuberculosis with a Ph.D. in Microbiology. Her research focuses on lipid-based biomarkers and the application of MALDI-TOF in Mycobacterium species. She has broad experience in TB diagnostics and molecular microbiology, and is currently exploring AI-assisted methods for rapid drug susceptibility testing.
This study demonstrates that MALDI-TOF lipid profiling, combined with machine learning, can differentiate DS from RIF-R or MDR Mtb strains based on distinct peak signatures, particularly in the 599, 810, and 1279 m/z regions. Although lipid analysis requires several steps, it may serve as a rapid and informative complement to conventional DST, especially in cases of treatment failure or delayed response, ultimately supporting better clinical decision-making.
Source: Conference 2024