INTRODUCING BIOALERTS™
Each year, over 700,000 patients die in US hospitals, and a large portion of those deaths are preventable through earlier recognition and intervention. Biocogniv's Bioalerts™ help frontline providers recognize acute conditions before they become irreversible, using only routine tests already performed at hospitals.
SEPSIS
Sepsis is the most costly condition and the #1 cause of death in US hospitals. However, no targeted therapy exists, and guidelines call for timely administration of antibiotics as soon as the condition is detected.
Biocogniv's Sepsis Bioalert™ can predict whether a patient is at high risk for sepsis when the condition is still not obvious to providers, avoiding the rush and disruption associated with the current standard of care based on last-minute detection.
our innovation engine
The confluence of large clinical databases and high-performance artificial intelligence (AI) models is enabling a new paradigm in medical diagnostics.
Biocogniv has built proprietary platforms and datasets that power in-silico clinical trials of unprecedented scale, allowing us to discover new opportunities without incurring the risk and high cost of traditional clinical trials.
TESTIMONIAL
"Having worked on novel biomarkers for decades, I am genuinely impressed and excited about Biocogniv’s ability to leverage routine blood tests to detect acute conditions before they become obvious. These Bioalerts could soon become part of the standard of care in emergency medicine, where we are constantly racing against time."
TESTIMONIAL
"I oversee innovation at an organization that employs 5,000 frontline providers at hundreds of hospitals, so we've seen many products. I believe Biocogniv's Sepsis Bioalert is a breakthrough in medicine as it goes beyond traditional alerts that merely point out what can be known without them – it identifies what is not clinically evident, as early as possible in the patient trajectory."
TESTIMONIAL
"We have worked on a blinded, independent validation of Biocogniv's Sepsis Bioalerts, using a large dataset from our 1,000-bed system. The accuracy of the predictions were in excellent agreement with the expected performance of the tool. I think this is going to change how Sepsis and many other acute conditions are approached by providers."
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