Each year, 30 million patients are incorrectly treated for infectious disease because of the time, frequently days, required with current techniques to establish an accurate diagnosis.

According the U.S. Centers for Disease Control, this time lag results in more than 225,000 deaths per year, including 100,000 deaths per year from infections acquired in hospitals. Delayed diagnosis is further estimated to cost the healthcare system more than $10B/year in extended hospital stays and overuse of antibiotics. Based on its ability to rapidly identify the specific strain of infectious organisms in a patient sample, the GSS technology has great potential to drastically reduce the time between diagnosis and treatment and enable the targeted use of anti-infectives for optimal effect.

In proof-of-concept demonstrations, GSS has been performed on clinical samples for more than 300 bacterial organisms representing species and strains of both gram-negative and gram-positive bacteria (including, Enterococcus, E. coli, Shigella, Salmonella, and Staphylococcus). The ability of GSS technology to identify and strain type these organisms has been demonstrated in a wide range of clinically relevant samples including blood cultures, and human stool.

GSS has also demonstrated the ability to discriminate among drug resistant and drug-susceptible strains of Staphylococcus aureus from clinical isolates. In the study, 52 unknown staph isolates from a Boston area hospital were combined with with samples of known sequence and genomic barcodes were generated. All strains were readily identified with clear differentiation of drug-resistant MRSA strains (USA100, USA300, USA400, and Mupirocin Resistant) from methicylin-susceptible strains (MSSA) as distinct clusters.