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It has long been evident that cancer is a heterogeneous disease, but only relatively recently have we come to realize the extent of this heterogeneity. No single therapy is effective for every patient with tumors having the same histology. A clinical strategy based on a single-therapy approach results in overtreatment for the majority of patients. Biomarkers can be considered as knives that dissect the disease ever more finely. The future of clinical research will be based on learning whether certain therapies are more appropriate than others for biomarker-defined subsets of patients. Therapies will eventually be tailored to narrow biomarker subsets. The ability to determine which therapies are appropriate for which patients requires information from biological science as well as empirical evidence from clinical trials. Neither is easy to achieve. Here we describe some nascent approaches for designing clinical trials that are biomarker-based and adaptive. Our focus is on adaptive trials that address many questions at once. In a way, these clinical experiments are themselves part of a much larger experiment: learning how (or whether it is possible) to design experiments that match patients in small subsets of disease with therapies that are especially effective and possibly even curative for them.

Reports from the 2010 Clinical and Translational Cancer Research Think Tank Meeting: Design Strategies for Personalized Therapy Trials