Destruction or dysfunction in the human pancreatic islet affects at least 23.6 million affected individuals in the U.S. alone. The inability to regulate insulin production and maintain glucose homeostasis leads to a variety of severe diabetic complications at an estimated 2007 US health care cost of $174 billion dollars. Although medical management, lifestyle changes, and pharmacological agents are successful treatment tools for some, they are less effective, and have failed, in those with unstable diabetes, indicating that an urgent need for alternative therapies exist. Pancreatic islet transplantation is a form of cellular replacement therapy that has been shown to restore glycometabolic control and render some patients insulin independent. Our long term goal is to therefore improve human islet survival and transplantation success rates by understanding the factors affecting cell function in-vitro and in-vivo both in the native pancreas and transplant environments.; A survey of the challenges and relevance of human pancreatic islets as a tool in diabetes research is first undertaken using descriptive statistics. Univariate and multivariable logistic regression (MLR) analysis was next used to show that a number of novel and established organ donor, pancreas processing, and islet isolation factors improve the odds of obtaining successful human islet isolation yields. This is an important finding because low islet yield is often the rate-limiting factor for wait-listed transplant recipients. Upon optimization of microarray processing and analysis methods, in a subset of transplant quality human islet preparations, we further demonstrate that genomic variability also exists between samples. This suggests the presence of donor-specific intrinsic islet factors that are distinct from those in our MLR model and is also noteworthy because an understanding of genetic variability in islet quality may help to improve inconsistent graft behavior post-transplant. Using differential equations to physiologically model human islet beta cell function, tools are then developed to assess genetic variability in the normal and diabetic state. Lastly, we demonstrate the feasibility of a national islet matching program by generating a set of mathematical formulas, based on factors previously identified, that are evaluated using experimental and simulated data. This is vital because single-center islet allocation procedures are inefficient and lead to limited availability. The algorithm is then implemented through a web-based automated cell distribution system and further examined prospectively using mixed statistical methods. A descriptive study to develop a standardized islet transportation protocol was then performed to ensure that matched islets could be shipped remotely to clinical research laboratories.; When taken together, these studies provide insight into factors affecting human pancreatic islets that may be used to improve therapeutic options for diabetes patients and expand the availability of the procedure.