The cancer cell line encyclopedia (CCLE), a joint academic and industry collaboration, provides a vast resource for analyzing the effectiveness of anti-cancer drugs across numerous cell lines. The predictive modeling of tumor sensitivity to targeted drugs has primarily focused on generating functions that map gene expressions and genetic mutation profiles to targeted drug sensitivity. The prediction accuracies of genomic signature based models are often limited as reported in initial analysis (Barretina et al.) of CCLE database. In this article, we illustrate that incorporating the target inhibition profile of the anticancer drugs and the functional behavior of related drugs will enable us to achieve much higher prediction accuracy.