U.S. service members are strong but they’re still people, and people get sick sometimes. But when one gets sick at the last minute, that can have serious repercussions on their unit’s ability to execute critical missions.
The Defense Threat Reduction Agency, or DTRA, is trying to get ahead of this problem by developing a predictive algorithm that knows whether a service member is falling ill—due to anything from a cold to exposure to biological weapons—up to 48 hours before they start to show any symptoms.
“Think of it as a check-engine for the human body,” Edward Argenta, science and technology manager for DTRA’s Joint Science and Technology Office, told Nextgov.
DTRA partnered with the Defense Innovation Unit to leverage the latter’s other transaction authority—a special procurement method outside of the Federal Acquisition Regulations—to develop the algorithm hand-in-hand with health IT company Royal Philips.
Using its own globally-collected data sets, Philips was able to develop a unique algorithm for the Defense Department. Using 165 distinct biomarkers across 41,000 cases, the Philips team was able to create the Rapid Analysis of Threat Exposure, or RATE, algorithm, which the company says can “predict infection 48 hours before clinical suspicion” with better than 85% accuracy.
“For comparison, this performance lies in between blood-based breast and prostate cancer screening tests, and an enzyme immunoassay based first-tier Lyme disease test,” according to a company release.
“By coupling large-scale data, with our experience in AI and remote patient monitoring with DTRA’s drive for innovation, we were able to develop a highly predictive early-warning algorithm based on non-invasively collected biomarkers,” Joe Frassica, chief medical officer and head of research for Philips North America, said in the release ..
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