Drug development field has been evolving from empirical medicine to precision or personalized medicine. The right treatment for the right patient population is the pursuit under Precision Medicine, while developing new medicine efficiently and effectively is the overarching charge for entire pharmaceutical industry. In the challenging environment, the application of novel statistical methodology that enable structured search of sub-population with enhanced treatment effect is useful, so are the enrichment and adaptive enrichment designs. In this presentation, we first share how Medimmune Biostatisticians are impacting on the company-wide Precision Medicine Initiative by introducing and enabling easy computation of advanced subgroup identification methods. We then discuss the merits of enrichment designs along with regulatory guidance and a case study. Lastly, we brief on the MedImmune/Johns Hopkins University collaboration project which has resulted in an adaptive enrichment design that combines elegant Bayesian subgroup-identification algorithm with our widely used compound Go/No Go decision criteria. With its novelty and practicality, this design is one of the novel approaches that we are proposing to apply in supporting the initiative of Precision Medicine in MedImmune.