In many critical healthcare situations, including sepsis and septic shock, the identification and diagnosis of infectious agents is burdensome and slow. Timely medical intervention is often delayed while laboratory testing is performed and the results analyzed. A point-of-care rapid diagnostic tool is a well-known unmet need within the clinical community. Some tools do exist, but they typically present limitations and draw-backs. Importantly, none give actionable results in the clinically relevant timeframe of 3-4hrs. Recently, UCSD researchers have developed an improved system for rapid gene profiling and diagnostic identification of infectious disease agents and their resistance profiles, by applying High Resolution Melt (HRM) technology and machine learning to a digital polymerase chain reaction (dPCR) platform.
UC San Diego researchers have developed a diagnostic platform, that uses universal digital PCR to perform 20,000 reactions simultaneously and High Resolution Melt (HRM) plus machine learning to analyze the reactions in real-time. In a blood sample containing a single organism or multiple organisms, this technology allows identification and quantitative concentration measurement for each infectious agent as well as several resistance genes within 4 hours, enabling evidence-based timely medical intervention.
This patent-pending technology allows rapid and quantitative analysis of clinical samples, at the bedside.
Precision medicine, Real-time, blood sample, Infectious disease, Bedside, Diagnostic, High Resolution Melt, digital PCR, Machine learning