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

Abstract

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.