  In this paper, we propose a virtual clinical trial for assessing the
performance and identifying risks in closed-loop diabetes treatments. Virtual
clinical trials enable fast and risk-free tests of many treatment variations
for large populations of fictive patients (represented by mathematical models).
We use closed-loop Monte Carlo simulation, implemented in high-performance
software and hardware, to quantify the uncertainty in treatment performance as
well as to compare the performance in different scenarios or of different
closed-loop treatments. Our software can be used for testing a wide variety of
control strategies ranging from heuristical approaches to nonlinear model
predictive control. We present an example of a virtual clinical trial with one
million patients over 52 weeks, and we use high-performance software and
hardware to conduct the virtual trial in 1 h and 22 min.
