becoming an important component in drug development [46], [47]. It is, therefore, possible to design precision medicine for individual patients based on their genomics profiles. Pharmacogenomics has gone beyond studying individuals’ drug response based on genome characteristics (e.g., copy number variations and somatic mutations) and now incorporates additional transcriptomic and metabolic features such as gene expression, considering factors that influence the concentration of a drug reaching its targets and factors associated with the drug targets. Since the gene expression profiles of cell lines are known to vary considerably in the process of prolonged culture under different culture conditions and techniques, the use of gene expression from cell lines for prediction of drug response in the patient is currently controversial. A recent algorithm for predicting in vivo drug response with the patient’s baseline gene expression profile achieved 60%– 80%predictive accuracy for different cases[48].Other research [49], [50] studied drug response using immunodeficient mice xenografted with human tumors, which have the advantage of potentially studying both genetic and nongenetic factors that affect cancer growth and therapy tolerance [51]. Similar pharmacogenomics studies are also important to vascular diseases. Although antiplatelet agents such as clopidogrel are widely prescribed for diseases such as acute coronary syndrome (ACS), their responses vary greatly from person to person and approximately30%of the patients may exhibit resistance to clopidogrel [52], 53]. Since clopidogrel is activated by thecitocromoP450(CYP)enzyme system to active metabolite, CYP2C19 loss-of-function (LOF) allele(s) affects the responsiveness of clopidogrel, but not the new antiplatelet agents (prasugrel and ticagrelor). Therefore, it is cost effective to use the genotype-guided method to screen carrier of CYP2C19 LOF allele(s) when using antiplatelets in high-risk ACS patients [54].