Recent advancements in consumer directed personal computing technology have led to the generation of biomedically-relevant data streams with potential health applications. This has catalyzed international interest in Patient Generated Health Data (PGHD), defined as "health-related data - including health history, symptoms, biometric data, treatment history, lifestyle choices, and other information-created, recorded, gathered, or inferred by or from patients or their designees (i.e. care partners or those who assist them) to help address a health concern."(Shapiro et al., 2012) PGHD offers several opportunities to improve the efficiency and output of clinical trials, particularly within oncology. These range from using PGHD to understand mechanisms of action of therapeutic strategies, to understanding and predicting treatment-related toxicity, to designing interventions to improve adherence and clinical outcomes. To facilitate the optimal use of PGHD, methodological research around considerations related to feasibility, validation, measure selection, and modeling of PGHD streams is needed. With successful integration, PGHD can catalyze the application of "big data" to cancer clinical research, creating both "n of 1" and population-level observations, and generating new insights into the nature of health and disease
