Bloodstream infections (BSIs) represent a very serious clinical manifestation that can be caused by a variety of bacterial and fungal pathogens, many of which have been associated with high rates of mortality. Physicians caring for patients with BSIs are challenged with having very limited time to make an effective diagnosis, including identification of the causative agent and determination of the antimicrobial susceptibility profile of that pathogen, prompting the use of empiric treatment regimens that routinely consist of multiple broad-spectrum antibiotics. Since a comprehensive diagnosis typically takes several days to complete, many patients receive antibiotics either unnecessarily or incorrectly, due to the lack of infection or infection with an antibiotic-resistant pathogen, respectively. Although currently unavoidable based on the diagnostic tools available, these therapeutic decisions can have severely detrimental implications on patient health, including the generation of antibiotic resistant organisms and the destruction of normal bacterial flora, the latter of which can give rise to additional downstream infections with pathogens such as Clostridium difficile. With these consequences in mind, it is clear that new and improved processes that expedite the detection of BSI-causing pathogens are vital to reducing patient mortality rates and enabling more effective antibiotic stewardship practices. The proposed studies focus on developing a rapid and efficient method to detect BSIs directly from human whole blood, effectively replacing standard blood culturing devices which can have extensive times-to-result. We will evaluate commercially available blood separation devices for their sample processing effectiveness for subsequent analysis in the BacterioScan 216Dx, a highly sensitive laser light-scattering device that has a ~3-log lower limit of detection (LOD) than instruments currently used in clinical microbiology laboratories. Once established, we will use this process to determine the limit of detection and time-to- positivity for a broad panel of common BSI-causing pathogens, comparing the 216Dx?s detection performance to that of a conventional blood culturing device. Based on preliminary data, we anticipate significant improvements in times required to flag samples as positive, without significant increases in pathogen LOD relative to currently-utilized methods. Likewise, we envision a reduced time to definitively identify uninfected specimens, promoting the justified de-escalation of unnecessary antimicrobial treatment. Taken together, particularly when considering the potentially dire clinical implications of BSIs, successful execution of this proposal will empower clinicians to make faster and more informed therapy decisions which, in turn, will impact both patient care and the more prudent use of antimicrobial agents.

Public Health Relevance

Current diagnostic tools for the detection of microbial bloodstream infections (BSIs) suffer from extended times-to-result, leading to unnecessary broad-spectrum antimicrobial therapy and jeopardizing patient health. Utilizing our proprietary laser light-scattering technology, we propose to expedite the BSI detection process to provide reliable results in a fraction of the time currently required in clinical practice. This improvement will not only reduce the mortality rate associated with BSIs, but will also enable antibiotic stewardship practices in support of preserving our current antibiotic armamentarium.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43AI136184-01
Application #
9465849
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ritchie, Alec
Project Start
2017-12-22
Project End
2018-11-30
Budget Start
2017-12-22
Budget End
2018-11-30
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Bacterioscan, Inc.
Department
Type
DUNS #
029599160
City
Saint Louis
State
MO
Country
United States
Zip Code
63108