Clinical trial design, management and data analysis is undergoing a data revolution. With the advent of integration of large scale Omic data sets ranging from Clinical-omics (EHR data) down to single cell omics, the data deluge has both been a boon and bane. This data is only helpful in improving in the design and management of clinical trials if we are able to appropriately analyze and interpret it. Clearly, the bottleneck is no longer the data generation but rather the data processing and insight generation from this data. This has given way to a boom in development of computational tools, platforms and methods to solve these challenges which are now being integrated into the daily working of these trials.