An in silico approach to treating “the right patient with the right drug at the right dose at the right time”

Biomarkers that predict responses to anti-cancer drugs are required to establish personalized cancer medicine, which is defined by the United States Federal Drug Administration as treating “the right patient with the right drug at the right dose at the right time” (1). In this issue, Dr. Wang and colleagues report a gene expression signature that predicts the efficacy of ZD-6474 (vandetanib) in 89 lung cancer cell lines (2) using a data set deposited in the cancer cell line encyclopedia (3). This was an in silico study; therefore, the results require validation in tumor samples from lung cancer patients treated with ZD-6474. However, the study provides a good example of a method of identifying candidate biomarkers that predict responses to anti-cancer drugs.