Type 2 diabetes (T2D) is characterised by hyperglycaemia, primarily due to insulin resistance and β-cell failure. Current therapeutic interventions, while initially beneficial, have little effect on disease progression as they are unable to combat the continued decline in β-cell function and mass.  We aim to identify a Gene Expression Signature (GES) that reflects the overall health of the β-cell. This GES will then be used to identify new anti-diabetic agents that are able to slow or prevent the progression of β-cell failure. To do this, we cultured INS1-E cells in control low glucose conditions (11.1mM, 72hrs) to represent a “non-diabetic” state, or high glucose conditions (20mM, 72hrs) to induce β-cell failure (decreased insulin secretion) and apoptosis (increased caspase 3/7 activity) thereby mimicking a “diabetic” state. We also treated cells with high glucose for 24hrs followed by the addition of a combination of anti-diabetic drugs (exendin-4, metformin and sodium salicylate -selected based on their ability to treat different aspects of β-cell dysfunction) for 48hrs to restore β-cell function, which represents a “successfully treated” state (32% restoration of insulin secretion, 43% reduction in apoptosis, n=20, p<0.05). Next generation sequencing was then used to establish gene expression profiles for each of the states. Significance Analysis of Microarrays (SAM) procedure was then performed to create a GES, consisting of an optimal set of genes that best defined the difference between the “diabetic” and “successfully treated” cell states. This resultant GES can predict the state of the cells with 100% accuracy. Therefore we have successfully generated a GES that is representative of β-cell function. This GES will be used as a novel tool to screen a compound library to identify agents that are able to restore β-cell function and enhance survival, and therefore may be able to slow or prevent the progression of T2D.