Twin Health, a startup in IIT Madras’ research park, has developed a method to monitor an individual’s health parameters by creating a digital twin.
The digital twin, created using 174 health markers and over 3,000 data points collected every day from the individual using sensors, helps the individual to monitor what they eat and how they live, thereby “reversing type 2 diabetes”, according to the claim of the architects of the study.
On Wednesday, at the IITMRP, the evaluation report of the experiment that included 206 prime patients and 82 persons in the controlled group, was tabled.
Twin Health uses AI to create a digital twin, which tracks metabolic health, includes 10 metabolic conditions such as diabetes, weight, bp, cholesterol, insulin resistance, kidney failures and diseases that affect the liver and pancreas. A coach assesses the data points, helping the individual lose body weight thereby increasing metabolism and physical activities. This enabled to reduce damage by almost 58%, according to the evaluation report.
An individual is subjected to a year-long treatment to monitor their health, diet, and medications. Each of the four-phase treatments is three months long. In the first three months the individual’s blood sugar is monitored and normalised, resulting in the healing of the underlying metabolism in the next three months. By the end of six months the organ health improves and by the 12th month, there is a sustained reversal of metabolic activities, the report said.
The startup enrolled 206 prime persons with type 2 diabetes in the random control group and 82 persons with T2D were enrolled as controlled patients. The latter did not follow the Twin Health process. The study found that over 90% of the precision treatment patients achieved normal blood sugar, stopped taking all diabetes medicine and were free of diabetes.
In a year 73% of the prime group achieved ‘remission’ compared to none in the control group, the report claimed. Also, over 50% reduction in cardiovascular events was noticed in the group. Over 50% of the twin precision treatment achieved normal systolic and diastolic bp levels within 3 months and 90% of them were not using any medication after the 30th day.
The programme categorises foods as red, orange and green. The study found that subjects in the prime group moved from the red and orange category to green foods ensuring continuous engagement and adherence to the programme.
According to the study authors the outcomes suggested that daily precision nutrition guidance using food intake data can be beneficial for individuals with metabolic disorders and type 2 diabetes.
Ashok Jhunjhunwala, president of IIT Madras Research Park, said as a borderline diabetic he participated in the experiment. He had difficulty in adjusting his vegetarian diet to meet the demands of the experiment. But at the end of it he said he not only shed a few kilos of weight but was more energetic and increased his working hours from 12 to 15 hours a day.