Introduction to Automated Insulin Delivery (AID) Algorithms
Automated Insulin Delivery (AID) algorithms are the core components of Artificial Pancreas systems, primarily utilizing Model Predictive Control (MPC) to forecast glucose trends and adjust insulin delivery proactively [1]. Historically, PID controllers were used, but the industry has shifted toward MPC (Tandem, Insulet) and Adaptive Learning (Beta Bionics) to manage the physiological lag of subcutaneous insulin [2].
Key Components of AID Algorithms
AID algorithms rely on several key components, including:
- Glucose Sensors: Continuous glucose monitoring systems that provide real-time glucose data [6].
- Insulin Pumps: Devices that deliver insulin based on the algorithm's calculations.
- Control Algorithms: The software that analyzes glucose data and adjusts insulin delivery.
Innovations in AID Algorithms
Recent innovations in AID algorithms include:
- Tandem Control-IQ: Integrates TypeZero's MPC for distinct sleep/activity profiles, allowing for more personalized insulin delivery [3].
- Medtronic 780G: Focuses on aggressive auto-correction boluses to improve glucose control [4].
- Beta Bionics: Eliminates carb counting via weight-based adaptive initialization, simplifying the insulin dosing process [5].
Challenges and Limitations
Despite the advancements in AID algorithms, there are still challenges and limitations to be addressed:
- Pharmacokinetic Lag: Insulin absorbs slower than food digests, limiting the algorithm's ability to flatten meal spikes without causing subsequent hypoglycemia [6].
- Data Dependency: Sensor compression lows or Bluetooth disconnects force systems into \