The data collected by computed tomography scanners, artificial pacemakers, glucose meters, MRI scanners, portable ECG monitors, and other medical devices allowed the experts to view every patient as a functioning biological and chemical system, the university’s press office explained. 

It was further added that the developed algorithms generate a prognosis of a body’s reaction to treatment and help to accurately determine what effect the treatment plan prescribed by the patient’s attending physician has on morbidity and mortality rates.

Upon completion of the preclinical studies and clinical trials, the scientists learned to choose the most optimal treatment model, the press office added. The new technology will allow to reduce patients’ treatment duration by at least 20 % and give doctors an opportunity to dedicate more time to other patients, a spokesperson stressed. In addition to that, the method makes it possible to minimize human error. 

“One of the most successful research directions explored by of our center’s scientists is creating a virtual simulation of homeostasis—a process by which an organism can adjust to changes in the external and internal environment. For example, such simulation allows to assess the risk of prostate cancer recurrence after initial treatment. Experimental studies give us the opportunity to predict disease progression even before the surgery and free up time for the doctor to attend the patient,” Alexander Suvorov, Chief Statistician at the Centre for Analysis of Complex Systems, was quoted by the press office as saying.

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