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.

With MelodyOne, it can be determined within a few hours which antibiotic is truly effective, compared to a typical two to three days. The device measures the vibrations of living bacteria on an ultra-thin carbon layer, immediately revealing whether an antibiotic is effective. This represents a significant step forward in faster and more targeted diagnostics, and in the fight against antibiotic resistance.

The jury praised the project’s innovation, collaboration, and scalability. Thanks to the grant, we can expand the pilot program to more patient samples and extend the testing period.

What does this mean ?
• Patients receive the right treatment faster
• Reduce unnecessary antibiotic use
• Reduce the risk of antibiotic resistance

“With this grant, we can test our technology in practice and bring faster diagnostics directly to patients.” – says Dr. Aleksandre Japaridze, CTO & Founder Soundcell.

This marks a huge step forward in faster and more targeted diagnostics — and in the fight against antibiotic resistance