Precision medicine is revolutionizing medical research and changing the way physicians treat patients based on the fact that there are subgroups of patients who are sensitive to or respond differently to treatments. In this talk, I will present two interesting clinical trial designs for precision medicine. First, I will introduce a group sequential enrichment design based on adaptive regression of response and survival time. This design starts by enrolling patients under broad eligibility criteria and continues by restricting enrollment to the most recent adaptively identified treatment-sensitive patients. At each interim decision, submodels for regression of response and survival time on a possibly high dimensional covariate vector and treatment are fit, variable selection is used to identify a covariate subvector that characterizes treatment-sensitive patients and determines a personalized benefit index, and comparative superiority and futility decisions are made. A simulation study shows that the proposed designs accurately identify the sensitive subpopulation if it exists and yields substantially higher power compared to a conventional all-comer group sequential design and existing enrichment designs. Second, I will talk about personalized risk-based screening design for comparative two-arm group sequential clinical trials. This design uses patients’ characteristics to change the treatment allocation probability during the trial and assign more patients to the best-performing individualized treatment, which is known as covariate-adjusted response adaptive randomization (CARA). I will discuss the challenges and opportunities in CARA performed in the context of group sequential design for comparative study and then talk about the proposed design as an effective way to address the challenges. A simulation study shows that the proposed design controls error rates and yields better clinical benefits compared to existing randomized controlled trial designs.