Accurately predicting the onset of disease is a major challenge in clinical medicine because the genesis of diseases is generally a complex and dynamic process. Wearable sensor technologies provide an unprecedented opportunity to collect physiological data at orders of magnitude higher high time-resolution than conventional clinical practice. This provides unprecedented opportunities for investigating the dynamics of disease processes and may usher in a new era of real-time, personalized medicine. We have proposed the potential of real-time, continuously measured physiological data as a non-invasive, “digital biomarker” approach for detecting the earliest stages in the transition to a disease state. In this talk, I will describe an example of our interdisciplinary team’s work on this topic that uses the early detection and possible prediction of febrile (i.e., fever-associated) adverse events in cancer events as an important application.
Prostate Cancer, General Oncology, Biomarkers in Oncology
• Biology of circulating, extracellular nucleic acids and translational applications
• Developing next generation approaches for early detection and monitoring of cancer
• Bioinformatics and computational biology, high-throughput sequencing
• New technologies to enable cancer detection and monitoring