Advances in sensing technologies embedded in wearables have enabled a growing array of available data endpoints, making wearables an increasingly valuable tool in drug development. Many of the early examples of wearables in clinical trials analyzed the exact output: number of steps taken and number of hours slept. However, researchers can glean more valuable insights from correlating the aggregate of data available from wearables data rather than isolating to an individual data point.

Correlating Wearables Data for Deeper Insights

Wearables data become much more interesting when activity and sleep data are correlated with other data being collected – inside and outside of office visits. This correlation can provide context as to why activity, sleep, or heart rate levels may have fluctuated. Sponsors can then uncover important patterns. For example, if a participant is less active on days that a medication dose is missed, or sleeps more after taking the medication, it could indicate drowsiness as a possible side effect.

This remote data can also serve as a useful indicator of behavioral health, providing researchers with a more objective means to understand how a participant may be feeling while taking a drug, supplementing participants’ direct, subjective feedback to researchers. Because there are strong correlations between activity and sleep levels with depression and other mental health conditions, wearables data can help researchers identify early signs and intervene accordingly. For example, a researcher can be alerted and proactively intervene if a participant begins sleeping more and becomes less active when taking a drug. These insights can be especially useful for manufacturers of drugs that have an increased risk of depressive or suicidal thoughts.

Integrating Real-time Data

But it’s not just the endpoints from wearables that enable drug developers to gain these holistic and objective insights. The game-changing benefit that wearables provide is the continuous, real-time and passive collection of data from participants.

“Most of the measures [wearables track] are relatively novel, not so much in the sense that we haven’t measured these things before, it’s just that we haven’t measured them with this frequency, this continuity and in the outpatient space,” said Zubin Eapen, M.D., M.H.S., chief medical officer of CareMore Health System and formerly of the Duke University Medical Center and the Duke Clinical Research Institute.

The ability to access continuous, near real-time data offers researchers the ability to gain more proactive insights into the effects a treatment is having on participants – which can present trends that would not otherwise be quickly or easily discerned. This can give researchers a deeper understanding of the specific impacts of a given treatment.

In addition to understanding how a drug is impacting participant behaviors like sleep and activity levels, wearables are also helping researchers understand how participants’ behaviors impact a drug’s efficacy. Researchers traditionally have not had a way of knowing about lifestyle changes between office visits unless a participant reported it. However, the continuous collection of data from wearables is providing more insights into this.

For example, wearables can provide intraday data (data that shows continuous activity over the course of a day) so that researchers can see the total number of steps taken in a day, the peaks in activity, and the duration of activity throughout the day. All of these can be an indicator that a participant started or stopped an exercise program. The researcher can be alerted based on this activity and determine what, if any, effect it has on the condition and the drug’s performance.

As we transition from episodic to continual data collection and drug developers increasingly recognize the benefits of wearables data beyond number of steps taken—the number of clinical trials utilizing the devices will grow significantly. A research report from Validic supports this, finding that 97 percent of pharma and CROs plan to utilize digital health technologies in trials more over the next five years.

And, as more trials begin making use of such digital technologies, we will continue to see new and interesting applications of wearables data emerge. When correlated with other clinical data, the power of wearables data stands to transform not just the drug development process, but also our understanding of health.

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