Artificial intelligence (AI) is transforming diabetes care, ushering in a new era of personalized treatment options that improve disease management and patient outcomes. This approach combines advanced algorithms with real-time data to provide more accurate, timely, and individualized care for people living with diabetes.
Closed-loop systems, commonly known as artificial pancreases, utilize AI algorithms to analyze CGM data and automatically adjust insulin delivery in real-time. These systems are typically used by individuals with type 1 diabetes whose pancreas cannot produce insulin. AI-driven systems such as artificial pancreases ensure that optimal insulin dosages are administered, effectively reducing the risk of hypoglycemia. Furthermore, their user experience has been significantly enhanced through mobile apps, enabling users to share live blood glucose data and insulin administration details with family members and healthcare providers, thereby facilitating patient-led self-management.
Several popular diabetes technology companies are at the forefront of this push towards AI in diabetes treatment. While these companies have slight variations in their integration of AI, they all serve the common goal of delivering timely and optimized doses of insulin to improve diabetes self-management. An essential component of these technologies is predictive modeling, a form of AI. These algorithms analyze data from CGMs, meals, and activity levels to predict future blood sugar levels and adjust insulin delivery. Similar to weather forecasts, they use trends from historical data to make future predictions. As more data is collected, these systems improve over time, reducing the need for manual interventions and making diabetes management easier.
Tandem’s X2 Insulin Pump uses Control-IQ technology to adjust insulin doses and keep blood glucose in range. Control-IQ can determine blood glucose levels up to 30 minutes in advance based on CGM data. This technology can automatically suspend insulin delivery when low blood sugar is predicted.
The iLET Bionic Pancreas by Beta Bionics uses its own “Bionic Pancreas” insulin-dosing algorithms to deliver corrected insulin doses based on signals from the CGM. This is also the first pump that determines the bolus insulin dose to be given, eliminating the need for user carb counting.
Similarly, Medtronic has developed a series of MiniMed Insulin Pumps, each with its defining features and FDA approvals for a specific diabetes type and age group. For example, the MiniMed 670G and 770G systems use SmartGuard technology to adjust insulin doses every 5 minutes and the Suspend on Low feature to stop insulin when glucose drops below a set level.
Omnipod’s tubeless insulin system, the Omnipod 5, delivers continuous insulin with a wearable Pod. It offers customizable glucose targets for personalized therapy and includes a “HypoProtect” mode to prevent exercise-induced low blood sugar.
While AI brings many benefits to diabetes care, it is important to acknowledge the associated risks. The large-scale collection and analysis of sensitive health data by AI systems creates concerns around data protection, unauthorized access, and potential misuse of personal information.
Additionally, AI models may lack adequate representation of certain racial minorities, socioeconomic groups, and lifestyles in their training datasets, leading to less accurate predictions for certain populations. This raises concerns about inclusivity and equitable care.
In conclusion, the integration of AI into diabetes treatment is bringing many new changes in care with personalized and innovative solutions. The use of artificial pancreases, particularly for those managing type 1 diabetes, has been clinically shown to improve health outcomes. However, it is essential to understand the associated risks that come with these technologies. As the field continues to evolve, AI holds great potential to bring transformative advancements to diabetes care.
