Collecting, processing and analyzing the ever-growing volume of online data has been one of the main forces driving advances in IT platforms for clinical trials. The wealth of data that can be obtained through everything from clinical sources to patient-worn sensors can help investigators identify potential trial participants, discover potential adverse events, and even provide data to regulators to support approvals for new indications.

As they look to incorporate this vast pool of information, clinical trial managers have found that legacy EDC technology isn't up to the task. Incorporating the full breadth of data into the trial data set, including from mHealth devices, requires more advanced systems built to deal with all the challenges this trove of data represents.

Former Oracle Health Sciences General Manager Steve Rosenberg spoke about this need in a recent Clinical Leader Live event. Rosenberg noted that there is "definitely a big push" to incorporate patient-generated data in trials; in some cases, from consumer-level sensors, but particularly from medical-grade sensors and devices that produce more accurate and precise data.

There are a plethora of such devices that capture information about things like movement, sleep, blood glucose levels, oxygen saturation, and more – information that has significant potential clinical value. These devices can be worn or used by patients at home or during their daily routines to allow continuous monitoring. They also can be at the clinic itself and make the collection of routine information easier and faster. Being able collect and process data from mHealth devices at the point of action is very valuable, Rosenberg said, "and to the extent it can be made convenient, the more important it becomes."