Hypothesis generating model-based wearable clinical trial

Wearable physiological sensors have the projected capability to detect unknown and unreported health conditions. Development requires rounds of discovery-oriented human subject research and confirmatory clinical trials. However, each study is a significant investment and difficult to justify in isolation. This impasse requires bootstrapping spiral device development through hypothesis-generating, model-based clinical trials. An unconventional clinical trial design addresses environmental health and infectious disease, through the day-to-day observation of diverse people who occupy a shared environment. The design utilizes a flexible suite of developmental diagnostic devices to detect the physiological impact of exposures. Through advanced data analysis, the devices provide information about deviations from normal parameters for each human subject. The correlation of these anomalies across the entire cohort generates hypotheses about exposures that impact health. These hypotheses can be investigated further in targeted studies and lead to simultaneous refinement of the devices.