New Peer-Reviewed Study in New England Journal of Medicine Catalyst Finds Twin Health's AI Precision Treatment Significantly Improves Outcomes in Patients with Type 2 Diabetes and Reduces Reliance on Costly Medications, Including GLP-1s

Cleveland Clinic-led study finds Twin Health's precision AI and hyper-personalized care outperforms standard diabetes treatment—reducing A1C, unhealthy weight, and medication use

MOUNTAIN VIEW, Calif., Aug. 20, 2025 /PRNewswire/ -- Today, Twin Health announced the publication of results from a Cleveland Clinic-led study in the New England Journal of Medicine Catalyst, evaluating its Twin Precision Treatment for the management of type 2 diabetes. The program features technology-driven interventions that leverage artificial intelligence to deliver personalized insights and lifestyle recommendations aimed at improving glycemic control and metabolic health in adults with type 2 diabetes. The findings, published today, showed that 71% of study participants using the Twin Precision Treatment system met the primary endpoint of achieving an A1C below 6.5% while eliminating most blood sugar-lowering medications, including glucagon-like peptide-1 (GLP-1) receptor agonists, sodium glucose cotransporter-2 (SGLT-2) inhibitors, dipeptidyl peptidase-4 (DPP-4) inhibitors, and insulin.

Type 2 diabetes affects nearly 1 in 10 Americans, and prolonged elevated blood sugar levels increase the risk of serious complications like heart disease, kidney failure, and stroke.

Twin Precision Treatment System Uses Artificial Intelligence, Machine Learning and Wearable Sensors for Sustainable Results

Developed by Twin Health, the Twin Precision Treatment combines digital twin AI with personalized clinical care, including licensed providers, nurses, and coaches. Using data from wearable sensors, the system continuously tracks real-time health metrics such as blood glucose levels, weight, blood pressure, stress, physical activity, and sleep. Users access these insights through a smartphone app, offering personalized nutrition and exercise guidance, encouraging patients to achieve their goals and sustainable health improvements. The specific app-generated dietary recommendations were based on AI-enabled predictions of each patient's blood glucose responses to specific meals.

"The study demonstrates that AI-driven precision medicine is the key to metabolic healing," said Dr. Lisa Shah, chief medical officer and executive vice president of Twin Health. "We're committed to our mission of producing real results for real people. This study is an important milestone on that journey and a glimpse into what's ahead for the future of metabolic care."

Kevin M. Pantalone, D.O., Director of Diabetes Initiatives at the Cleveland Clinic and a professor of medicine at the Cleveland Clinic Lerner College of Medicine, served as the primary investigator for this study. For the clinical trial (NCT05181449), researchers aimed to determine whether Twin Health's Twin Precision Treatment system could help individuals with type 2 diabetes, managed in a primary care setting, achieve their blood sugar goals while also eliminating glucose-lowering medications.

"In routine clinical practice, type 2 diabetes is often treated with a one-size-fits-all approach where individuals are prescribed medications and told to 'watch their diet and stay active," said Dr. Pantalone. "Our study demonstrated the AI-enabled system of sensors to understand each patient's unique metabolic profile, and AI-enabled human care team coaching facilitated significant improvements in glycemic control, weight loss, and quality of life versus usual care, while allowing marked de-escalation of glucose-lowering medications. Interventions like this system can help patients make informed, lasting lifestyle changes to control their blood sugar and sustain weight loss."

Dr. Pantalone collaborated with a team of 13 primary care physicians to recruit 150 patients from the Cleveland Clinic Twinsburg Family Health Center located in Twinsburg, Ohio. Of these, 100 were assigned to the Twin Precision Treatment group and 50 to the standard of care group. On average, patients were 58.5 years old, had been living with type 2 diabetes for about nine years, and presented with a mean body mass index (BMI) of 35.1 and an average A1C level of 7.2%.

The primary endpoint was to see how many participants reached an A1C below 6.5%  after 12 months without needing any glucose-lowering medications except for metformin, a common low-cost diabetes medication.

After one year, a majority of study participants in the Twin intervention group achieved an A1C below 6.5%

After one year, 71% of participants enrolled in the intervention group lowered their A1C levels below the 6.5% threshold, while taking only metformin. By comparison, only 2.4% of participants receiving standard care achieved the same result.

Participants in the Twin intervention group also lost more weight (8.6% vs 4.6% of body weight) while significantly reducing their reliance on medications:

• GLP-1 Receptor Agonist medication use decreased from 41% to 6% among participants
• SGLT-2 Inhibitor use decreased from 27% to 1% of participants
• Dipeptidyl peptidase-4 (DPP-4) inhibitor use decreased from 33% to 3% in participants
• Insulin use decreased from 24% to 13% among participants

The quality of life scores and treatment satisfaction were notably better for those using the Twin Precision Treatment, highlighting its potential as a highly effective and sustainable option for diabetes management.

Real-World Reduction in GLP-1 Use
In the Cleveland Clinic-led study, 85% of participants in the Twin Health program eliminated GLP-1s, demonstrating that many individuals can sustain clinical goals without long-term dependence.

Translating Clinical Success into Cost Savings
Twin Health is proven effective for diabetes, weight loss and metabolic health comorbidities, including hypertension. Twin Health's real-world results echo the RCT findings, delivering over $8,000 in average first-year savings per member. These savings result from reducing reliance on high-cost medications, such as GLP-1s, and avoiding unnecessary care utilization, making Twin a scalable and cost-effective solution for employers and health plans seeking to address the growing burden of metabolic disease.

About Twin Health
Twin Health's AI digital twin technology creates a real-time model of each individual's unique metabolism using data from smart devices, lab results, and meal logs. This model provides personalized guidance on nutrition, activity, sleep, and more, supported by a compassionate clinical team. Twin's AI digital twin and human care work in synergy, providing a continuous new standard of care for metabolic health. For employers and health plans, Twin delivers $8.0K+ in annualized savings per member by safely reducing reliance on high-cost medications and lowering avoidable medical utilization. Twin's clinical results for diabetes, weight loss and metabolic health co-morbidities, including hypertension, are peer-reviewed and published in top journals, including the New England Journal of Medicine Catalyst and those of the American Heart Association, American Diabetes Association, and American College of Cardiology. Learn more at https://usa.twinhealth.com.

Press Contact
Alex McKechnie
AOX3 for Twin Health
[email protected]
475.399.4056

SOURCE Twin Health