Wearables Create a New World of Data for Clinical R&D
To understand the safety and efficacy of treatments, researchers typically rely on data collected during clinical-trial site visits. This includes data from clinical procedures performed by investigators and patient-reported outcomes like health-related quality-of-life questionnaires.
While this data has long been considered the best available, it is far from perfect. In the clinic setting patients are subject to white-coat hypertension, which occurs when a patient exhibits increased anxiety levels, including abnormally high blood pressure, resulting from being in a medical environment. And completing periodic assessments, like questionnaires and diaries, introduces the possibility of recall bias and other subjective factors that may skew data.
Now a new method of data collection is available that offers study teams a more complete data set, one that may paint a more complete picture of the patient and may open up myriad possibilities to better understand outcomes.
By equipping patients with biosensors, wearable devices and mobile apps, clinical R&D teams have the opportunity to gain unprecedented insight about the patient experience by combining biometric and activity data with traditional site-based and patient-reported outcomes data. When captured with the appropriate controls in place (to ensure privacy and security), this asset can be used to improve the quality of life for all of us.
As the use and availability of convenient and unobtrusive devices like wristbands and patches continues to grow, we are expecting to see more mobile health tools used in clinical trials. IDC, a market research firm, is forecasting a compound annual growth rate for wearables of 45% from 2014 to 2019, when it is expected to hit 126 million units. As we've seen in recent years, this high demand spurs innovation that makes wearable devices easier to use with ever more sophisticated sensor technology—
advances that can certainly benefit clinical trials.
Today more than two-thirds of Americans use smartphones and even higher percentages of people use them in countries like the United Kingdom, Germany, France, Japan and South Korea, so the pool of technology-competent patients is increasing globally.
Why is this important?
Data from patients using wearables offers great promise for clinical R&D for several reasons:
1. Assessment of disease progression, including identification of “digital” biomarkers that can provide indications of whether patients are getting better or worse
2. Assessment of response to therapy
3. Symptom and/or adverse event identification, and ultimately, prediction
Furthermore, the ability to jointly investigate the biometric and activity data of subpopulations has the potential to uncover insights, patterns and trends that hadn't previously been visible, potentially deepening our understanding of how best to treat disease. In addition, mobile-health data forms a “digital biospecimen” that can be stored and re-evaluated in the future to test alternate hypotheses.
For patients choosing to enroll in clinical trials, mHealth provides a more convenient and engaging way to participate in clinical research that advances the development of important new therapies. The requirement of needing to visit a physician investigator may, over time, be reduced, potentially easing the burden on sponsors of subject recruitment and retention. Patients may be subjected to fewer data-collection procedures and they may ultimately be able to gain access to richer and more insightful data about their clinical progression.
While it's easy to get caught up in inflated expectations of the typical technology hype cycle (visions of virtual trials, crowd sourcing, etc.), the industry should seek to enhance the existing trial model by incorporating an mHealth device in an increasing number of trials. This should be done thoughtfully and with careful attention to regulatory dialogue—sponsors will need to evaluate devices for the quality of the data, patient compliance and clinical relevance. In addition, they will need to have a plan for how they will gather and manage the data collected by these devices and they'll need an approach for analyzing it to understand potential signals and insights.
To better understand the opportunities and challenges associated with mHealth, Medidata sponsored a trial, MOVE-2014, to explore the impact of equipping type-2 diabetes patients with smartphones and activity trackers. We wanted to understand whether health outcomes—in this case, changes in a measure of blood glucose as well as changes in weight—were impacted by the use of these tools.
We gained great insight by sponsoring our own study, including the need to focus on analytics in three areas: patient compliance, data quality and clinical insights. Throughout this process we came across a number of questions some of which can be answered with sophisticated data science tools and techniques while others require the collaboration of industry, academia and regulators to assess both value and risk. Ultimately, we'll need to work toward an understanding of whether mobile health data meets the scientific rigor required of clinical R&D.
The deep potential in mHealth data is due, in part, to its novel set of characteristics: It's objective, real world, eSource, remote, real-time and continuous. By analyzing this data in context with other sources, both site-reported and patient-reported, the industry may find answers to wide-ranging clinical questions. For example, if a patient complains of a headache, can his or her sleeping patterns or exercise habits from a specific point in time inform treatment decisions?
It is incumbent on all stakeholders—including industry, academia, regulators, patients and the tech industry—to explore this exciting new world of wearables data.
Kara Dennis is managing director of mobile health for Medidata Solutions.