By Omar Ford, Staff Writer
Health care data analytics start-up Intensix Ltd. brought in $8.3 million in its series A funding round. The Netanya, Israel-based company has developed a real-time predictive analytics platform for the early detection of patient deterioration in the intensive care unit (ICU) and high acuity departments of hospitals. Pitango Venture Capital led the round.
The funding will be used to boost the company’s sales and marketing operations in North America and to expand and accelerate the development of its predictive analytics platform.
Intensix was founded by Gal Salomon, who also serves as its CEO.
The company’s platform uses advanced mathematical algorithms to create models for early predictions of deterioration and or complications for patients in the ICU. Driven by prediction models derived from big data analysis and an advanced high-dimensional analytics technique, the company said its predictive platform has the flexibility to manage large patient populations without losing individualized treatment needs.
Intensix said that data ranging from vital signs to historical and demographic data goes into the system and is run through a set of models and results in predictions.
Salomon previously founded software security-specialist Discretix Technologies Ltd., a company, he helmed and sold to Arm Holdings plc for $75 million in 2015.
“There are unexplained events that we really can’t understand, but we have a lot of data [on],” Salomon, told Medical Device Daily. “What we’re trying to do is provide early warning signs for patients that are in the ICU.”
He added that there are often lots of complications in the ICU and that it was the company’s goal to catch some of these complications before they occur. But first the product must get on the market. Salomon noted that the technology would not need to be approved by the FDA and could be on the market by the end of the year.
BIG DATA, BIG COLLABORATIONS
With an influx of data flooding the market via electronic health records, sensors and medical devices, physicians now have untold amounts of information on patients. As a result, the health care data analytics market is quickly growing, set to reach $24.55 billion by 2021 from $7.39 billion in 2016 at a change of growth rate of 27.1 percent from 2016 to 2021, according to a report from Markets & Markets.
The question now becomes how can harnessed patient data lead to something useful?
IBM Watson Health has perhaps been one of the biggest names at the forefront of the big data analytics conversation. The Armonk, N.Y.-based company turned heads last month when it revealed it would team up with the FDA to define a way to exchange health data across a variety of technology platforms with an initial focus on oncology data. (See Medical Device Daily, Jan. 12, 2017.) The project is intended to empower patients with the ability to have easy and routine access to all of their own health care information, including making it portable and shareable.
IBM Watson has also teamed up with Dublin-based Medtronic plc to develop Sugar.IQ, a diabetes monitoring app. It’s based on a 10,000-patient database of information from Medtronic.
In the past few years, Intensix has made strides in harnessing its patient analytics platform through studies and collaborations.
In February 2016, the company began a study of the impact of sepsis in the ICU. The study uses a database of more than 600 billion pieces of patient data. Data from the study comes from the medical information collected on some 8,000 patients at the Sourasky Medical Center in Tel Aviv, Israel, as well as several American hospitals, between 2007 and 2014.
Data from the study showed the platform could recognize deterioration before care teams notice it might occur.
A month after announcing its sepsis study, the company revealed it had entered a partnership with the Mayo Clinic to study early predictions of life-threatening complications in a critical care setting. The study will focus on the feasibility of using the Intensix platform to predict patient deterioration associated with infection in the ICU.