Abstract
Clinical trials are fundamental for advances in cancer treatment. The traditional framework of phase 1 to 3 trials is designed for incremental advances between regimens. However, our ability to understand and treat cancer has evolved with the increase in drugs targeting an expanding array of therapeutic targets, the development of progressively comprehensive data sets, and emerging computational analytics, all of which are reshaping our treatment strategies. A more robust linkage between drugs and underlying cancer biology is blurring historical lines that define trials on the basis of cancer type. The complexity of the molecular basis of cancer, coupled with manifold variations in clinical status, is driving the individually tailored use of combinations of precision targeted drugs. This approach is spawning a new era of clinical trial types. Although most care is delivered in a community setting, large centers support real-time multi-omic analytics and their integrated interpretation by using machine learning in the context of real-world data sets. Coupling the analytic capabilities of large centers to the tailored delivery of therapy in the community is forging a paradigm that is optimizing service for patients. Understanding the importance of these evolving trends across the health care spectrum will affect our treatment of cancer in the future and is the focus of this review.