Over the last decade, billions of dollars have been invested in digital health solutions that apply broad-stroke guidance for individuals with type 2 diabetes. Many of these generalized solutions don’t work — they’re not personalized, and are therefore not sustainable. 

Twin Health has an entirely different perspective on treating chronic conditions, and it’s focused on the individual.

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Now, our approach is supported by even stronger evidence.

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A clinical trial conducted at the Cleveland Clinic – widely recognized as one of the nation’s leaders in diabetes care – and peer-reviewed and published in New England Journal of Medicine Catalyst has demonstrated that Twin Health’s AI digital twin technology can do what other solutions cannot: deliver results that exceed gold-standard traditional clinical care. The Twin approach helped those with type 2 diabetes significantly improve glycemic control, lose weight, reduce reliance on expensive medications, and enhance their quality of life. 

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These results come at a critical point in time for the U.S. healthcare industry. One in ten Americans lives with type 2 diabetes. And while this complex condition is the product of many individual factors like genetics, diet, lifestyle, and environment, the root cause is often a dysfunctional metabolism.

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Our AI digital twin™ technology creates a real-time model of a member’s unique metabolism, allowing our clinical team to deliver small, achievable lifestyle recommendations that drive lasting results. In this paper, we’ll explore the groundbreaking results of our study at the Cleveland Clinic, which provides compelling evidence to validate our approach to metabolic care. We’re pleased to share it with you. 

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Sincerely, 

Jahangir Mohammed, Founder and CEO, Twin Health 

Lisa Shah, MD, Chief Medical Officer & EVP, Twin Health
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Landmark study of AI digital twin™ for diabetes

The study, conducted at the Cleveland Clinic’s Twinsburg Family Health and Surgery Center, evaluated the effectiveness of AI digital twin™ technology for type 2 diabetes management in a primary care setting — the first randomized, controlled trial of its kind. The trial, which was designed to mirror real-world clinical practice, enrolled 150 adults with type 2 diabetes who had lived with the condition for a median of nine years. This population was intentionally selected to be representative of individuals for whom traditional treatments had fallen short. Key participant characteristics included: 

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• Average Age: 58.5 years
• Median BMI: 35.1 kg/m2 (indicative of obesity)
• Average HbA1c: 7.2% (above the recommended target for diabetes management)

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The primary goal of the study was ambitious: to help participants achieve an HbA1c level below 6.5% — the diagnostic threshold for diabetes — without the use of glucose-lowering medications except metformin within a year. 
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The intervention: Twin Health vs. traditional care

Participants in the study were randomized into two distinct groups. 

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The Twin Health Group received access to Twin Health’s Digital Twin platform, which delivers precise, real-time insights about the individual’s metabolism. Using AI and machine learning to analyze continuous health data, Twin Health’s platform created AI digital twins (digital replicas of their metabolic function) which then provided personalized lifestyle and diet recommendations. 

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Key elements of the intervention for the Twin Health Group included: 

• Sensor technology. Participants were given four smart devices that communicated data to Twin Health’s platform: a continuous glucose monitor, an activity sensor, a smart scale, and a smart blood pressure monitor. 
• Twin Health app. Using data from sensors, lab results, and user inputs, Twin’s platform created digital twins of participants’ metabolisms.
• Personalized dietary guidance. Participants were asked to eat until satisfied, without calorie restrictions. Foods were categorized within the app as “recommended,” “eat in moderation,” or “discouraged” based on their metabolic impact. The app’s barcode-scanning feature helped participants categorize foods. 
• A compassionate care team. Participants received ongoing guidance from a Twin Health coach, ensuring that recommendations were both practical and personalized. 

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The Traditional Care Group, the control group, received standard diabetes care as determined by their primary care provider, without additional interventions or study-directed influence, ensuring their study experience mirrored the real-world experience of conventional diabetes care. 
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The Twin Health Difference 

Unlike traditional one-size-fits-all approaches to diabetes management, Twin Health’s AI continuously adjusts recommendations based on members’ metabolic responses over time. Everyone’s metabolism is different, and while some people may tolerate bread well, others may experience significant blood sugar spikes. The AI digital twin™ refines its recommendations accordingly, allowing members to safely eat to satiety without strict calorie limits — an approach that proved highly effective in this study. 
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The results: ‘compelling evidence’ for digital twin technology

The study’s results are irrefutable: Twin Health’s AI digital twin™ technology is a powerful, non-pharmacological approach to diabetes management. 

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The study authors found the following: 

• 71% Twin Health participants achieved an HbA1c below 6.5% without glucose-lowering medications. These participants effectively healed their metabolisms with Twin Health in the span of a year. Only 2.4% of participants in the Traditional Care Group achieved the same result. 
• More than half  of Twin Health participants maintained this outcome for at least 90 days prior to the one-year endpoint – a sustained success rate far beyond what’s seen in standard care. Only 2.8% of control group participants achieved this same result.  

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These findings demonstrate the potential of Twin Health’s AI digital twin™ technology to transform diabetes care by offering individuals a highly personalized path to metabolic healing while reducing reliance on expensive medications. 
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Diving deeper: key study results

Medication elimination in the Twin Health group at one year

• GLP-1 receptor agonists: Usage dropped from 41 → 6 participants, an 85% reduction.
• DPP-4 inhibitors: Usage dropped from 33 → 3 participants, a 91% reduction.
• Sulfonylureas: Usage dropped from 31 → 17 participants, a 45% reduction.
• SGLT-2 inhibitors: Usage dropped from 27 → 1 participant, a 96% reduction.
• Insulin: Usage dropped from 24 → 13 participants, a 46% reduction.
• Usual-care group: Medication use either remained stable or increased

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Key health metrics at one year 

• Average weight loss: −27 lbs (Twin Health) vs. −14 lbs (Usual care)
• HbA1c: −1.3% (Twin Health) vs. −0.3% (Usual care). This is a massive improvement over standard care delivered at one of the best clinical centers of excellence in the country.

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Rx-free remission

19% of Twin Health participants achieved and maintained an HbA1c below 6.5% for at least 3 months after stopping all glucose-lowering medications (except metformin). Only 1% of control group participants achieved this result.

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Quality of life and treatment satisfaction

Significant improvements in both quality of life and treatment satisfaction were seen only in the Twin Health group. The study authors noted that improvements, measured using the Audit of Diabetes Dependent Quality of Life (ADDQOL) and the Diabetes Treatment Satisfaction Questionnaire (DTSQs) were statistically significant for Twin Health participants at both 6 and 12 months.
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What do these results mean? 

For decades, type 2 diabetes management has been centered on medication management. Prescriptions that lower blood sugar, produce more insulin, or suppress appetite were the only tools clinicians had to help their patients — and those only address the symptoms of metabolic dysfunction. Twin Health’s Cleveland Clinic study demonstrates how a personalized, data-driven approach to behavior change can usher in a new era of type 2 diabetes treatment.

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Lower Blood Sugar: One of the most striking results of the study was the 1.3% average reduction in HbA1c among Twin Health participants, over four times the reduction seen in the control group – and achieved on top of Cleveland Clinic’s already exemplary standard of care. Research shows that for every 1% reduction in HbA1c, the risk of diabetes-related health complications drop significantly:  

• 21% lower risk of diabetes-related death
• 14% lower risk of heart attack 
• 37% lower risk of kidney disease and other microvascular complications

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Sustainable Weight Loss: Weight loss is often recommended for those with type 2 diabetes, but few interventions (including GLP-1s) deliver meaningful, sustainable results for everyone. In this study, Twin Health participants lost an average of 8.6% of their body weight — nearly double the weight loss seen in the control group. Research shows losing just 5% of body weight can improve insulin sensitivity, reduce inflammation, and lower cardiovascular risk. 

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Medication Cessation: Twin participants’ need for medications like GLP-1s and SGLT-2 inhibitors dropped dramatically, by 85% and 96%, respectively. These dramatic reductions are not just statistically significant; they represent a massive potential savings for the healthcare system. But they also raise a critical question for healthcare providers: How much are we spending on medications that may not be effective (or necessary) when individuals can achieve and maintain good metabolic health through tracking their unique lifestyle responses? 

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The implications are clear. Type 2 diabetes doesn’t have to be a lifelong diagnosis. Twin Health is helping individuals take control of their health, reduce their dependence on medications, and achieve metabolic healing without compromising happiness. 
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What this means for you 

• For Employers
  
  • Lower diabetes-related healthcare costs through sustainable metabolic healing 
  • Improve employee well-being and quality of life with a trusted solution backed by gold-standard clinical research
• For Health Plans
  
  • Implement a proven, scalable solution for reducing chronic disease 
  • Support value-based care models with sustainable outcomes and enhance the strength of your provider network
• For Individuals
  
  • An achievable, personalized roadmap to lasting metabolic health 
  • Enjoy more food freedom and a better quality of life

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A new standard for metabolic health 

This Cleveland Clinic study demonstrates that Twin Health is a breakthrough treatment.  

With the power of digital twin AI, Twin Health doesn’t just help individuals manage their diabetes. It helps them achieve lasting metabolic healing. The majority of study participants in the Twin Health Group did what is generally believed to be impossible: they lowered their HbA1c below the diabetes threshold while reducing or eliminating medications altogether. No other solution on the market has delivered outcomes of this magnitude. 

This is more than just an incremental improvement in diabetes management. It’s a new standard of care. Rather than apply one-size-fits-all solutions, Twin Health addresses the root causes of metabolic dysfunction with personalized, data-driven interventions tailored to the individual. 

Cleveland Clinic’s study authors believe that digital twin technology has the potential to impact chronic conditions beyond metabolic disease. Bolstered by this compelling new evidence, Twin Health will continue to produce real results for real people. 

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