Precision medicine is the systematic use of information pertaining to an individual patient to select or optimize the patient’s preventative and therapeutic care. In recent literature, biomarkers have been classified to predictive biomarkers and prognostic biomarkers based one their role in clinical studies. To design a clinical trial for precision medicine, one should include both predictive and prognostic biomarkers. In this talk, we will propose a new family of covariate-adjusted response-adaptive designs, which incorporate these biomarkers as well as the responses. It is worth to point out that the predictive biomarkers and prognostic biomarkers play different roles in the new designs. Advantages of the proposed methods are demonstrated through both theoretical and numerical studies. Some further statistical issues are also discussed.