‘Digital Twin’ tech reverses type 2 diabetes, fixes metabolic disruptions

A novel artificial intelligence (AI) platform that integrates multidimensional data to deliver precision nutrition and health recommendations not only helps to induce remission in type 2 diabetes (T2D) but also to normalize a range of glycaemic and extraglycaemic parameters, as shown in a study presented at the 82nd American Diabetes Association (ADA) Scientific Sessions.

Known as the Whole-Body Digital Twin, the tech platform creates a digital representation of a patient using a combination of wearable sensor data, blood test readings, and self-reported information. It continuously updates and analyses the patient’s metabolic profile to identify problem areas and accordingly suggest changes in nutrition, sleep, activity and breathing, with the goal of reversal and prevention of multiple chronic metabolic diseases.

The twin precision treatment technology (TPT) platform was tested in 319 patients (mean age 45 years, mean diabetes duration 3.9 years) who had a mean haemoglobin A1c levels of 9 percent at baseline. These patients were randomized to undergo treatment with TPT or standard care for 6 months.

Interim analysis of 262 patients who completed the study (TPT n=199; standard care n=63) showed that TPT-led treatment facilitated ADA-defined diabetes remission in 83.9 percent of the patients, said lead study author Dr Paramesh Shamanna, who runs the Bangalore Diabetes Centre in India.

HbA1C dropped by 3.3 percent (95 percent confidence interval [CI], –3.6 to –3; p<0.001) over 6 months with TPT and only by a mere 0.39 percent with standard care (95 percent CI, –0.73 to –0.043; p=0.028), with the between-group difference being statistically significant (p=0.0001). [ADA 2022, abstract 4-LB]

Most patients (94.9 percent) in the TPT group lowered their HbA1C to <6.5 percent, achieved freedom from glucose-lowering medications, or required metformin only. All nine insulin users in the study were able to eliminate insulin requirement within 90 days.

Moreover, in a separate analysis of 199 patients, Shamanna and colleagues found that certain glycaemic and extraglycaemic parameters normalized with TPT.  

“There was a significant increase in the number of people having normal ranges at 90 and 180 days compared to baseline,” Shamanna said.

At 6 months, HbA1C, fasting plasma glucose, and Glucose Management Indicator, cardiovascular disease (CVD) risk score, NAFLD fibrosis score, atherosclerotic CVD risk score, and high sensitivity C-reactive protein were all within the normal range in about ≥90 percent of the patients. [ADA 2022, abstract 221-LB]

Meanwhile, the proportion of patients who were in the normal range for Homeostasis Model Assessment (HOMA)2B, HOMA2-Insulin Resistance, body mass index, waist circumference, ratio of triglycerides to high-density lipoprotein cholesterol, small dense low-density lipoprotein, and nonalcoholic fatty liver disease liver fat score varied between 60 percent and 90 percent.

“Our study demonstrates the diverse metabolic benefits which can be obtained with Whole-Body Digital Twin-enabled precision nutrition in addition to diabetes remission,” according to Shamanna.

Given the findings, the AI platform is expected to break the mould of the conventional, medication-driven management of T2D.

“The impact of the [Digital Twin] program on patient satisfaction, quality of life, and total cost of care is substantial and holds significant promise for large populations suffering from metabolic disease globally,” Shamanna said.