Abstract

ARTIFICIAL PANCREAS AND CLOSED-LOOP INSULIN DELIVERY SYSTEMS: THE FUTURE OF DIABETES TREATMENT

Komal Suresh Age*, Prafull Prakash Patil, Avadhut Sidhgonda Athanikar, Chaitali Abhijeet Shinde, Wavhal Omkar and Gadhave Sahil Uttam

ABSTRACT

The advent of the artificial pancreas and closed-loop insulin delivery systems represents a revolutionary step in managing diabetes mellitus. These technologies aim to provide better glucose regulation, reducing the risk of hypo- and hyperglycemia. By automating insulin delivery, they reduce the burden on patients and improve adherence to therapy. Recent advances in sensor technology, control algorithms, and machine learning have enhanced system accuracy, allowing for more precise glucose management. This review highlights the design, working principles, clinical efficacy, and future directions of artificial pancreas systems, emphasizing their potential to enhance patient outcomes and quality of life. Furthermore, we discuss the challenges related to cost, regulatory approval, and patient education, which must be addressed to ensure broader accessibility and long-term success of these systems. The artificial pancreas represents a significant advancement over traditional diabetes management methods, which rely on manual insulin administration and continuous glucose monitoring. Closed-loop insulin delivery systems mimic the function of a healthy pancreas by automatically adjusting insulin doses based on real-time glucose readings. This closed-loop approach improves glucose control and alleviates the mental and physical burden on patients who otherwise must monitor their blood sugar levels throughout the day. One of the key innovations driving the success of artificial pancreas systems is the development of advanced algorithms. These algorithms use complex mathematical models to predict glucose trends and adjust insulin delivery accordingly. Machine learning has further refined these models by enabling adaptive learning from individual patient data, improving accuracy, and minimizing errors. As a result, patients experience fewer episodes of hypoglycemia and better overall glucose stability.

Keywords: .