For individuals living with diabetes, monitoring blood glucose has classically been accomplished in an open-loop fashion through the utilization of a continuous glucose monitor (CGM), finger stick method, or both. A closed-loop artificial pancreas (AP) system has the potential to significantly reduce the burdens of type 1 diabetes (T1DM) patients. Creating a fully closed-loop automated insulin delivery system involves a progression from in silico studies, to clinical trials, and finally to outpatient studies to assess the system’s ability to cope with the challenges of daily life. Outpatient studies are currently being performed to evaluate the difficulties presented by meals, exercise, and nighttime glycemic control. Other studies are attempting to determine if benefit lies in a dual-chamber system that delivers both insulin and glucagon. Three components constitute an AP system: a CGM, an insulin pump, and a control algorithm that calculates insulin dosing based on the input from the CGM. There are currently three leading algorithms in the field of AP research: model predictive control (MPC), proportional-integral-derivative (PID), and fuzzy logic (FL). All three algorithms have shown high success rates in the field of AP research and are being studied in order to fine-tune control of blood glucose variability. In addition, the development of auxiliary safety systems is being pursued as means of diminishing insulin dosing error (1,2). In making the AP system a highly mobile, outpatient device, consumer electronics and technology such as 3G and Wi-Fi are being leveraged in the development of remote monitoring platforms to assist those living with diabetes. Smartphones may be used as a platform for the AP system, while 3G and Wi-Fi allow physicians to monitor patients with diabetes online from distant locations. However, the usefulness and costs of such remote monitoring features remain a controversial subject in healthcare. The past year has brought notable advancements in the field of AP research. Systems currently in development and testing phases may transform diabetes care from an open-loop, selfmonitoring routine to a fully automated closed-loop process where an individual with diabetes may be relieved from paying constant attention to their condition. Past clinical trials are being moved to outpatient studies, representing a significant leap toward a marketable AP consumer product. As current studies are constantly challenging AP technology, new limitations reveal areas for progression, innovation, and improvement. The following articles highlight this year’s most significant and intriguing strides toward ‘‘closing the loop’’ and show promise for the future of diabetes care.