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High-Precision Antimicrobial Resistance Detection Technologies Compatible with Automated Systems

An innovative technology rapidly and accurately identifies three drug-resistant bacteria (carbapenem-non-susceptible viridans group streptococci and H. influenzae, and PRGBS) that are easily misidentified in standard testing.

Advantages

‐ High Diagnostic Accuracy: Ensures reliable detection of reduced susceptible strains with high sensitivity and specificity overcoming misidentification in conventional automated systems.
‐ Prevention of Clinical Misidentification: Supports the selection of appropriate antimicrobial agents for clinically important bacteria with reduced susceptibility.
‐ Compatibility with Automated Testing Equipment: Offers excellent adaptability for seamless integration into existing automated susceptibility testing devices and selective media products.
‐ Solid Scientific Foundation: Backed by strong evidence based on molecular analysis of resistance mechanisms.

Current Stage and Key Data

Validation studies using clinical isolates completed; ready for implementation into automated susceptibility testing systems.
- Carbapenem-non-susceptible Viridans Group Streptococci: Clearly distinguished non-susceptible strains from susceptible strains based on growth inhibitory zone diameters.
- Carbapenem-non-susceptible H. influenzae: Achieved >90% sensitivity in detecting non-susceptible strains using a unique combination of antimicrobial agents.
- PRGBS: Reached 0.973 sensitivity and 0.989 specificity via a two-step algorithm (approx. 16% improvement in specificity compared to conventional methods).

Partnaring Model

Patent licensing, joint development, and technical collaboration for integrating technologies into automated systems and media products.
- Potential partners: Manufacturers of automated susceptibility testing systems, clinical selective media/reagents, and clinical diagnostic solutions.

Background

In recent years, the emergence of carbapenem-non-susceptible Viridans group streptococci and Haemophilus influenzae, along with PRGBS, has raised significant global concern. However, current automated susceptibility testing devices suffer from insufficient diagnostic accuracy, leading to frequent misidentifications and missed opportunities for appropriate treatment. To prevent the spread of resistance and optimize antimicrobial therapy, there is an urgent demand for advanced technologies that enable rapid, accurate detection of these resistant bacteria on automated platforms.

Principal Investigator

Kouji Kmura (Graduate School of Medicine, Nagoya University, Tokai National Higher Education and Research System)

Patents and Publications

- Patent pending

Project No:bk-05555