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August 12, 2019

Fluid Imaging Technologies and U of Colo. aim to automate bacterial findings

Courtesy / Fluid Imaging Technologies The FlowCam Nano imaging system from Fluid Imaging Technologies in Scarborough will be used in research conducted by Dr. Theodore Randolph of the University of Colorado. The instrumentation will help to automatically determine bacterial species in blood for fast, lifesaving treatment.

Scarborough laboratory instrumentation manufacturer Fluid Imaging Technologies and the University of Colorado Boulder have entered into an exclusive research agreement that aims to automatically identify bacterial species for fast, life-saving treatment.

The university has developed proprietary artificial intelligence software. The goal of the research is to determine whether the software can detect bloodborne bacteria and identify the species from images collected using Fluid Imaging Technologies’ FlowCam nano-imaging system, according to a news release.

The outcome could mean that sepsis due to staph, strep, listeria, E. coli and other bacterial infections may soon be detected much earlier.

Fluid Imaging Technologies is led by CEO Kent Peterson, a 2008 Mainebiz Business Leader of the Year.

Bacterial sepsis is costly

In the study, researchers plan to evaluate the 10 strains of bacteria most responsible for the 1.5 million sepsis cases and 250,000 fatalities annually in the United States according to Centers for Disease Control data. Those cases cost upwards of $6 billion in annual Medicare payments, according to the Centers for Medicare and Medicaid Services. 

The study will be conducted under the university's principal investigator, Dr. Theodore Randolph. The nano-imaging system will be used to create microscopic images, which will serve as “training set data.” The university's software will use the images to “train” a computer to identify the microorganisms automatically. 

Ultimately, the research team hopes the FlowCam system will reduce the time required to correctly identify the bacterial species causing an infection from several days in a laboratory to 60 minutes or less on-site. 

Once identified, the proper antibiotic may be prescribed for fast, effective treatment.

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