Hematological diseases affect millions of people annually. They include genetic disorders like hereditary spherocytosis, G6PD deficiency, and conditions related to HIV, sickle cell disease, in addition to blood cell cancers. Fundamental understanding of the intricate dynamics showcased by the cells would help us in disease detection and even provide vital information regarding the pathophysiology of the disease. Recently, there has been a tremendous interest in identifying biomarkers for cell-based diseases. Furthermore, microfluidic platforms and miniaturized lab-on-a-chip devices have made a considerable impact on point-of-care blood analysis, leading to effective diagnosis. Here, we focus on the numerical modelling of red blood cells (RBCs) in health and disease. A three dimensional, high fidelity in-silico RBC model capable of capturing hemodynamics has been developed. Dissipative particle dynamics (DPD) and the theories of statistical mechanics are implemented to analyze the cell behaviour and morphology in microcirculation. After the completion of the rigorous model validation process, an in-depth comparison of cell mechanics in different pathological states is examined.