NEW YORK – Prenosis on Wednesday said it will use $4.8 million from two Small Business Innovation Research (SBIR) grants from the National Institutes of Health's National Institute of General Medical Sciences (NIGMS) to study why patients develop sepsis in acute care settings and how best to treat them using its Immunix Artificial Intelligence platform.
Prenosis has built a knowledgebase on infection in acute care that comprises biomarker and clinical data from electronic medical records and 75,000 biological samples from 19,000 patients. The firm uses machine-learning algorithms trained on these data to capture patients' complex health states.
The Chicago-based spinout from the University of Illinois at Urbana-Champaign provides decision support tools using its platform to help doctors tailor antibiotic treatments according to patients' immune profiles. Additionally, Prenosis' Sepsis ImmunoScore, which also runs on the Immunix platform, gauges clinical parameters and protein biomarkers to estimate a patient's risk of sepsis within 24 hours.
The exact causes and evolution of sepsis are poorly understood. The syndrome is characterized by a dysregulated response to infection and is a leading cause of mortality in US hospitals. Prenosis is hoping to improve the knowledgebase in this regard and use the grants it recently received from NIGMS for two projects, entitled "Combined Biomarker and EMR Data for Heterogeneous Treatment Effects and Surrogate Endpoints in Sepsis", and "Use of Time Series Biomarker and Clinical Data to Construct a Time Trajectory Host Response Map."
"The outcomes of these studies could usher in a new era of predictive diagnostics, clinical decision support tools, improved clinical trials, and precision medicine drugs for sepsis," the company said in a statement.
Prenosis previously won a $749,000 Biomedical Advanced Research and Development Authority (BARDA) contract to demonstrate the clinical value of Sepsis ImmunoScore and $4.3 million from the US Department of Defense to develop technology for early point-of-care sepsis detection.
"When a patient enters the hospital, we want to provide more efficient treatment based on the individual biology of the patient," Prenosis CEO Bobby Reddy Jr. said in a statement. "Our uniquely robust dataset and machine learning platform holds the promise of linking patient biology to optimal care."