Autoimmune diseases occur when the body's natural defense system fails to differentiate its own cells from the foreign cells and mistakenly attacks the healthy cells. Among the autoimmune diseases, the most common serious disease is the type 1 diabetes (T1D). Biomarkers like c-peptide, autoantibodies, and glycated molecules are now widely used for the early diagnosis of diabetes. However, the diverse nature of biomarkers and the available autoantibodies as biomarkers are not enough to differentiate the heterogeneity inherent in T1D. Novel biomarkers have allowed the introduction of bioinformatics for assimilating the new data into clinical tools. Computer-aided drug design contributes to the discovery of novel autoantibodies, and molecular docking promises to enhance it. Moreover, the study of the pathophysiology of diabetes via molecular simulation has been proposed. In this review article, we focus on the characterization of the etiology, epidemiological factors, and mechanisms of hyperglycemia that induce cellular damage due to oxidative stress and proinflammatory responses. We also decribe novel biomarkers used for the detection of β-cell destruction and diagnosis at early stages. Bioinformatics tools including molecular docking, sequence alignment, and homology modeling are also presented. This report supports researchers in drug design, in disease detection at an early phase, and in therapy development for T1D-associated complications.