University Of Colorado Signs Fluid Imaging Technologies To Market Breakthrough Artificial Intelligence Technology For Identification Of Waterborne, Bloodborne Bacteria
In Exclusive Licensing Agreement, Company's FlowCam Nano Particle Imaging and Analysis System to Apply Patented AI
Global laboratory instrumentation manufacturer Fluid Imaging Technologies, Scarborough, ME and the University of Colorado have entered into an exclusive patent licensing agreement aiming for the automated detection and identification of waterborne and bloodborne bacteria, as well as thousands of other types of microorganisms and particulates. Under the terms of the agreement, the company is to commercialize the University's patented artificial intelligence software as the exclusive, worldwide licensee for applications involving the detection and monitoring of bacteria for detection and/or diagnosis of infections in blood and other bodily fluids, and for monitoring and detection of microorganisms and particulates in marine, freshwater, inland water bodies, municipal facilities, and other water applications. The company plans to cut the time required for physicians to correctly identify the bacterial species causing a sepsis infection from several days to 60 minutes or less, enabling the proper antibiotic to be selected and treatment to begin faster than currently possible. The agreement also names the company as worldwide licensee for applications involving particle detection and monitoring in the oil and gas industry.
Applying the University's U.S. Patent #62/712,970, “System and Method for Diagnosis of Infection”, the company plans to offer its patented FlowCam Nano particle imaging and analysis system with the artificial intelligence software as fully integrated functionality. The FlowCam Nano is the world's first flow imaging particle analyzer that automatically detects, images and characterizes micron- and sub-micron size particles and microorganisms ranging in size from 300 nm to 10+ µm. Combining the FlowCam's high-resolution, Nano-Flow Imaging microscopy images with the University's deep convolutional neural network software is to yield unprecedented speed and accuracy in the detection and identification of waterborne and bloodborne particles and microorganisms, according to the company.
Source: Fluid Imaging Technologies