Cancer is a deadly disease and a huge burden to the society. Although the last 60 years has seen improvements in cancer diagnostics, treatment strategies against most of the complex malignancies have not lived up to the mark. In the drug discovery area, the attrition rates have spiraled out of control, indicating that there is certainly something amiss employing the current research approaches against cancer. Advances in computational biology have revealed that cancer is a disease arising from aberrations in complex biological networks and its understanding requires more information than that obtained from the reductionist strategies. Similarly, magic bullet drugs that are designed against a single pathway may not impact these highly intertwined and robust cancer networks. In order to rein in cancer, one has to revamp the concepts in understanding the mechanism of cancer and drastically reform the present approaches to drug discovery. The idea behind this review is to enlighten the readers about the emerging concept of 'Network Pharmacology' in drug discovery. Network technologies have allowed not only in the rational targeting of aberrant signaling in cancer but also helped in understanding secondary drug effects. Concepts in network methods that are helping hit identification, lead selection, optimizing drug efficacy, as well as minimizing side-effects are discussed. Finally, some of the successful network-based drug development strategies are shown through the examples cancer.