SoundCell has published its latest results in collaboration with its partners at Reinier Haga Medical Diagnostic Center and TU Delft in the journal of ACS Sensors.
Current tools like MALDI-TOF or traditional antimicrobial susceptibility tests require separate workflows – one for identifying bacteria and another for determining antibiotic susceptibility. This leads to delays when every hour matters. In our latest scientific publication, we build on our single-cell diagnostic approach that does both simultaneously!
By combining graphene-based nanomotion sensing with machine learning, we can identify pathogens and detect antibiotic resistance within just a few hours. Our models differentiated E. coli, S. aureus, and K. pneumoniae with near 90% accuracy, and detected resistant vs. susceptible E. coli to meropenem antibiotic with more than >97% accuracy.
Read the full paper here.
