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Twin Health Secures $53M to Advance AI Digital Twin for Diabetes, Obesity

Twin Health

Employers and health plans look to Twin to meet growing demand for responsible GLP-1 strategies and long-term cost reduction

Twin Health, the AI digital twin pioneer for metabolic health, announced a $53M investment led by Maj Invest of Denmark. The funds will accelerate Twin’s expansion among health plans and Fortune 500 clients in retail, healthcare, financial services, technology and manufacturing. This week, the company also announced the results of a landmark study in the New England Journal of Medicine Catalyst that found Twin Health’s AI digital twin is a highly effective treatment for diabetes and weight loss, without high-cost medications.

“Diabetes and obesity are among the world’s biggest health challenges. For decades, we have invested in cutting-edge solutions to address the epidemic of metabolic disease,” said Jeppe Christianson, CEO of Maj Invest. “Twin Health represents a paradigm shift in diabetes and obesity care – one that is precise to each individual and scalable for employers and health plans.”

A Smarter Path to Diabetes Reversal, Weight Loss and Metabolic Health

Most metabolic health solutions have failed to deliver clinically meaningful outcomes and have increased healthcare spending because they rely on medications and extreme diets. Twin Health’s breakthrough is the creation of a real-time AI digital twin for each member. The digital twin is built from thousands of data points across biomarkers, behaviors, and preferences, reflecting not just a member’s metabolism but also their habits in nutrition, sleep, and physical activity. Twin provides continuous, high-performance care for metabolic health by optimizing biology and behavior in unison.

“Traditional solutions have focused on just managing the disease,” said Jahangir Mohammed, founder and CEO of Twin Health. “Twin is different. We address the root causes of chronic metabolic diseases to improve and reverse diabetes. Members use their own biomarker data—not population averages — to create their own AI digital twin that guides them in a way that is engaging, precise, and sustainable. We believe metabolic health is a continuous condition, not an episodic event, and Twin delivers continuous, 24/7 guidance to meet that reality. We envision a future where everyone has an AI digital twin to improve their health and reduce healthcare spend.”

Also Read: Komodo Health Launches Marmot AI to Speed Healthcare Innovation

Personalized and Human-Centered Care

Twin Health’s unique “healthy and happy” AI model is brought to life by combining technology and dedicated human care teams to treat metabolic disease in real time. Members receive daily, personalized guidance and live coaching to help them achieve their health goals —whether that’s lowering A1C, reaching a healthier weight, or safely transitioning off medications, including GLP-1s. Twin’s human care goes far beyond coaching. It is continuous, clinically guided care that adapts to members in real time. Twin is built on member choice, offering personalized support to those who seek a medication-free path to better health.

Built for Scale and Sustainable Results

Twin Health is a leader in performance-based care, offering results-driven pricing for employers and health plans. Clients only pay when members achieve meaningful clinical outcomes, such as A1C reduction, weight loss, or medication elimination. If milestones aren’t met, there’s no cost. With millions of eligible lives across its customer base, 90%+ retention, under 1% voluntary churn, and industry-leading conversion rates, Twin outperforms traditional care.

Meet Market Demand for Responsible GLP-1 Use

As GLP-1 usage skyrockets, Twin Health enables employers and health plans to implement responsible, evidence-based programs. Twin identifies eligible members, supports appropriate GLP-1 use where clinically necessary, and provides a personalized off-ramp to eliminate reliance on medications over time–ensuring members achieve and sustain their health goals without long-term medication dependence.

Source: PRNewswire

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