Animal Research for Type 2 Diabetes Mellitus, Its Limited Translation for Clinical Benefit, and the Way Forward

Obesity and type 2 diabetes mellitus (T2DM) have reached pandemic proportions worldwide, and considerable research efforts have been dedicated to investigating disease pathology and therapeutic options. The two hallmark features of T2DM, insulin resistance and pancreatic dysfunction, have been studied extensively by using various animal models. Despite the knowledge acquired from such models, particularly mechanistic discoveries that sometimes mimic human T2DM mechanisms or pathways, many details of human T2DM pathogenesis remain unknown, therapeutic options remain limited, and a cure has eluded research. Emerging human data have raised concern regarding inter-species differences at many levels (e.g. in gene regulation, pancreatic cytoarchitecture, glucose transport, and insulin secretion regulation), and the subsequent impact of these differences on the clinical translation of animal research findings. Therefore, it is important to recognise and address the translational gap between basic animal-based research and the clinical advances needed to prevent and treat T2DM. The purpose of this report is to identify some limitations of T2DM animal research, and to propose how greater human relevance and applicability of hypothesis-driven basic T2DM research could be achieved through the use of human-based data acquisition at various biological levels. This report addresses how in vitro, in vivo and in silico technologies could be used to investigate particular aspects of human glucose regulation. We do not propose that T2DM animal research has been without value in the identification of mechanisms, pathways, or potential targets for therapies, nor do we claim that human-based methods can provide all the answers. We recognise that the ultimate goal of T2DM animal research is to identify ways to advance the prevention, recognition and treatment of T2DM in humans, but postulate that this is where the use of animal models falls short, despite decades of effort. The best way to achieve this goal is by prioritising human-centred research.