As demand grows for alternatives to costly GLP-1 therapies, AI-powered “digital twins” are emerging as a novel approach to managing chronic metabolic conditions such as diabetes and obesity. Startups like Twin Health are combining wearable sensor data with machine learning to create individualized metabolic models that guide real-time lifestyle interventions.
By continuously analyzing biomarkers and behavioral inputs, these virtual replicas aim to support sustained weight loss and glycemic control without pharmacologic therapy. Early patient experiences suggest that personalized, data-driven recommendations may help overcome the limitations of traditional diet-based approaches, offering a scalable, non-drug pathway for long-term chronic disease management.