The rapid success of using human big data has been a novel trend for drug development and discovery. The human genetic techniques including Coding GWAS are generically associated with diseases whereas the expansion of Human Data Ecosystem in multi-geographic regions provide valuable insights on disease specific cohorts and genomic data. The investment on human genome research and analytics based on health records is expanding globally, with a more strategic approach to accessing human data. The research into Big Human Data Investment has their continuing synergistic influence for testing or generation and validation of hypothesis from the understanding of diseases to experimental validation in human samples and data.
In addition, the data from population specific variants could identify novel genetic associations with diseases, and also,the compilation of big data has a huge impact on the pharmaceutical industry’s research methods by using rapid analysis on demand with sufficient statistical power to derive future potential hypotheses. Since the deliverable from biobank analysis provides both disease risk and safety in the general population, the Biobank scale genomic data identifies rare variants such as the Loss of Function (LoF) variant that is associated with health.
In subgroups, the functional variants (Missense, LoF) accelerate medical development by reinforcing already validated and enriched genomic data sets where the potential of providing the opportunities for new drug indications and discovery. With more innovation and evolution we are closer to greater successes in the generation of diverse population genome data and at the same time deriving safety information and discovering new indications for drugs.