Advances in our understanding of the intricate molecular mechanisms for transformation of a normal cell to a cancer cell, and the aberrant control of complementary pathways, have presented a much more complex set of challenges for the diagnostic and therapeutic disciplines than originally appreciated. The oncology field has entered an era of personalized medicine where treatment selection for each cancer patient is becoming individualized or customized. This advance reflects the molecular and genetic composition of the tumors and progress in biomarker technology, which allow us to align the most appropriate treatment according to the patient's disease. There is a worldwide acceptance that advances in our ability to identify predictive biomarkers and provide them as companion diagnostics for stratifying and subgrouping patients represents the next leap forward in improving the quality of clinical care in oncology. As such, we are progressing from a population-based empirical 'one drug fits all' treatment model, to a focused personalized approach where rational companion diagnostic tests support the drug's clinical utility by identifying the most responsive patient subgroup.