Table 1.
Main Advantages and Disadvantages of the Currently Most Widely Used Algorithms of Hybrid and Experimental Full AID Systems.
| Algorithm | Advantages | Disadvantages | Applied in |
|---|---|---|---|
| PID | - Simple and straightforward, only calculation of the individual components P, I, D | – Only insufficient suited for regulating large glucose rises and falls (eg, after meals, during physical activity) | - Medtronic MiniMed 670G/770G/ 780G |
| - No complex simulation | - Only input of static parameters, such as insulin duration of action (information on pharmacokinetics according to insulin manufacturer) | ||
| - Initial input of few parameters: Carb/Insulin factors, insulin action time | - Does not take into account inter- and intra-individual variability of patients | ||
| – Great experience in controlling technical systems (eg, heating systems) | – No predictive calculation of the effect of insulin delivery on future glucose levels | ||
| MPC | - Dynamic model of the control process, does justice to the dynamics of insulin delivery control | – Only conditionally suitable for regulating of large glucose rises and falls (eg, after meals, physical activity etc.) | - CamAPS FX (Cambridge App) |
| - Prospective calculation of glucose level based on current insulin dosage (simulation by iteration) | – The complex model requires initial input of several parameters (eg, basal rate under CSII) | - iAP (Collaboration Universities Padova, Virginia, Santa Barbara) | |
| – Dynamics of the effect of different insulin doses is taken into account | - Diabeloop DBLG1 (self-learning by applying methods of artificial intelligence) | ||
| - Takes into account inaccuracies in glucose measurement and delays in insulin absorption | - Tandem CONTOL IQ | ||
| - Insulet Omnipod 5 | |||
| Fuzzy-Logic: MD-Logic (DREAMED) | - Simulates glucose regulation, adapted to physiological insulin delivery (combination of “Control to Range” and “Control to Goal”) | - Requires a fuzzy logic controller, in which treatment rules have to be implemented, making the development of the corresponding affiliation function is a challenge | - Cooperation with Medtronic regarding implementation in the future full AID system |
| - Fuzzy logic approximates the physiological behavior of an individual patient (adaptation of control parameters) | |||
| - Algorithm is self-learning | |||
| - Suitable for regulation of large glucose rises and falls (eg, meals, physical activity) and thus also suitable for delivery of meal boli |