  The development of a fully autonomous artificial pancreas system (APS) to
independently regulate the glucose levels of a patient with Type 1 diabetes has
been a long-standing goal of diabetes research. A significant barrier to
progress is the difficulty of testing new control algorithms and safety
features, since clinical trials are time- and resource-intensive. To facilitate
ease of validation, we propose an open-source APS testbed by integrating APS
controllers with two state-of-the-art glucose simulators and a novel fault
injection engine. The testbed is able to reproduce the blood glucose
trajectories of real patients from a clinical trial conducted over six months.
We evaluate the performance of two closed-loop control algorithms (OpenAPS and
Basal Bolus) using the testbed and find that more advanced control algorithms
are able to keep blood glucose in a safe region 93.49% and 79.46% of the time
on average, compared with 66.18% of the time for the clinical trial. The fault
injection engine simulates the real recalls and adverse events reported to the
U.S. Food and Drug Administration (FDA) and demonstrates the resilience of the
controller in hazardous conditions. We used the testbed to generate 25 years of
synthetic data representing 20 different patient profiles with realistic
adverse event scenarios, which would have been expensive and risky to collect
in a clinical trial. The proposed testbed is a valid tool that can be used by
the research community to demonstrate the effectiveness of different control
algorithms and safety features for APS.
