In modern drug development, identification of biomarkers and surrogate endpoints is becoming more important in many aspects of research and development. Predictive biomarkers can help accelerate development of a new drug for precision medicine by identifying subgroups of patients that will benefit more of the new treatment. Surrogate endpoints are intermediate endpoints (often based on biomarkers) that are highly predictive of clinical outcomes. They can be used in lieu of clinical outcome variables to measure the efficacy of a new treatment in clinical trials, in an effort to expedite the development of the new treatment. In this presentation, we will discuss the statistical methods and challenges in assessing biomarkers and surrogate endpoints from the industry perspective. Real examples will be used to illustrate the points. In particular, we will discuss a case study of the evaluation of surrogate endpoint for a herpes zoster vaccine using both of the Prentice criteria and causal inference framework.