Tag Archive for: digital trackers

Can Digital Wearables Help in Clinical Trials?

Today’s healthcare consumer can log and produce a range of data through wearable devices, smart fabrics, and intelligent sensors that are worn on the body or incorporated into garments and accessories, such as wristbands and watches. To date, wearables have been limited to tracking information related to health and fitness, but as the technology behind wearables for healthcare evolves, there is a growing interest in its potential in medical settings. New wearables show promise for addressing a range of medical conditions from diabetes to dementia. When applied to clinical trials, wearable technology is a potentially powerful research tool to gather clinical data in real-time and provide remote patient monitoring.

digital wearables

photo from http://www.alivecor.com/home

The clinical trials process could be optimized by leveraging existing smart technology, such as electrocardiogram (ECG) monitors like AliveCor, which enables anytime recording of ECGs; and smart pill technology (also known as “ingestibles”) which allows for both wireless patient monitoring and diagnostic imaging. Digital health company Proteus Digital has developed FDA approved wearable and ingestible sensors that work together to detect ingestions and physiologic data. The sensor is taken alongside medications, and is powered by the body’s biochemistry. The patch, body-worn and disposable, receives the data from the ingestible sensor, tracking medication-taking, steps, activity, rest, and heart rate and forwards that information to a Bluetooth enabled mobile device. If life science companies can get enough insight early in development, they can potentially create a more efficient drug development process and prioritize resources for the most promising therapies, with the goal of getting effective drugs to market faster.

Clinical use adoption will depend on ease of use, relevance and accuracy. Google’s life sciences division at Google X is in the process of developing a wearable health sensor specifically for use in clinical trials. The developers, who have already created a glucose-sensing contact lens, want to see how a continuous stream of medical-grade measurements of biological signals could be used to help earlier diagnosis or intervention in disease. The prototype wrist-worn sensor measures pulse, activity level, and skin temperature, alongside environmental information like light exposure and noise levels. Right now, it isn’t clear how Google’s prototype device will collect, analyse, and interpret data and incorporate information into a clinical trial data feed.  Issues of data standards and security will also need to be worked through. Google is in the early stages of the project, which will work with academic researchers and drug makers to test the wristband’s accuracy and seek regulatory clearance in the U.S. and Europe. The project will also draw on Google’s ongoing Baseline study, a medical and genomics project involving Stanford University and Duke University, which aims to map a healthy human body. Google Baseline will use a combination of genetic testing and digital health sensors to collect “baseline” data on healthy people. The project aims to establish genetic biomarkers relating to how we metabolize food, nutrients and drugs, how fast our hearts beat under stress, and how chemical reactions change the behavior of our genes.

Google’s wearable prototype, and other similar existing wearable devices, could give researchers insights that are currently only available intermittently (e.g. via a diagnostic test, or when a patient is being observed in a clinical setting).   Using sensors and wearables, drug efficacy and clinical trials outcomes might be better assessed through a variety of data points. It also allows for more objective measurement of data. For instance, obtaining objective metrics of hours of sleep in a clinical trial can be difficult to measure in a traditional trial setting when patients record this information at home. Being able to measure hours of sleep objectively through a wearable device could provide more complete data, although researchers still need to consider the context within which all data is captured. Having structured analysis of supplementary data may provide the additional evidence needed to show the benefits of a certain drug. However, more data does not necessarily translate into better data. The use of a wearable device alone does not add value to the clinical trial process. The real value lies in the ability to extract raw data and leverage real-time analytics to monitor trial progress in the moment, thereby facilitating early intervention which may reduce trial risks. In addition, continuous tracking of vital signs outside of a laboratory provides patients with better support through remote patient monitoring. Wearable technology’s transformative potential therefore lies not with the wearable itself, but with the real-time response to the data it collects.

As the healthcare ecosystem continues to shift to patient-centered care, a key consideration in designing the clinical trial of the future is the ability to make the process highly responsive and seamlessly connected to the patient’s every-day life. Currently the clinical trials process is inconvenient for participants; both in terms of time spent travelling to and from the trial location, and the time required to log physiological and drug reactions. Wearable devices can reduce the number of times patients need to go to a clinic and can provide a better, fuller picture of physiological data needed to measure a drug’s impact. Medidata and Garmin are collaborating to use Garmin’s activity tracker —the vivofit — in clinical studies. The vivofit measures steps taken, calories burned, and hours slept to capture patient data during clinical trials 24/7, without the need for clinic visits. The clinical trial data it collects is integrated with the Medidata Clinical Cloud repository that includes information such as vitals, medical histories, laboratories, and adverse events. Used in this way, wearables not only lead to increased data, but through remote monitoring, can reduce interruptions in a volunteer’s day.

Clinical trials are often criticized for not being sufficiently patient-centric. Innovating through the use of wearable devices can address this challenge by streamlining the process and creating greater patient engagement. The Clinical Innovation team at Eli Lilly recently offered a glimpse into the future through an interactive and immersive clinical trial simulation for Stanford Medicine X conference attendees. The team highlighted design considerations for remote clinical trials, as well as working prototypes for a mobile patient trial app, provider trial app, and a medical-grade biosensor. In order to contextualize and make data actionable, the design team at Eli Lilly is working on a closed-loop system that triggers an alert when certain metric points are activated, thereby allowing for real-time adjustments to be made.

Making the clinical trial process more convenient and connected through wearable devices could potentially explode the sample size of clinical studies, not just numerically, but also in terms of diversity – gender, ethnic, geographic, economic. We might then begin to get a more stratified picture of individual variation; hard to do with current methods of traditional clinical studies. The large uptake of Apple’s ResearchKit (an open source software framework for app development) on its release earlier this year, signals a greater willingness to take part in research when tools are designed to make participation easier. Within a day of ResearchKit’s launch, 11,000 volunteers signed up for a Stanford University cardiovascular trial; an unprecedented uptake. At the time, Stanford said it would normally take a national year-long effort to get that kind of scale.  However impressive these numbers are, a large test sample only matters if there are enough quality results. Furthermore, diversity is compromised if lower socioeconomic populations are excluded through restricting sampling to people that are iPhone users. If the very people who tend to be most affected by chronic diseases are excluded, research will be skewed toward a demographic that is markedly different than the one typically affected by the target disease. Still the future looks hopeful. With any study, there are challenges around how representative the study cohort is. The expectation is that smartphone apps, wearable devices, and biosensors can make the clinical trials process more responsive to volunteers, expand recruitment, and make the data source richer.

Challenges and Opportunities

The clinical trial of the future will increasingly take place outside the walls of the clinic. Tailored to the patient’s lifestyle, wearables can lead to increased patient engagement and ultimately bigger and smarter data. Trial volunteers will wear a device that continuously measures their activity and provides a complete picture of movement without having to disrupt their day. Physicians and researchers will have access to a much richer, more objective data set, thereby providing a real-world, real-time measure of patient physiology and how a drug affects quality of life. This will allow us to have a more holistic view of the patient than we have ever had before.

Wearables are emerging as a tool for creating a more responsive and efficient clinical trial process. At the same time, wearable devices can increase the volume and speed of data collection through a more seamless collection of large quantities of longitudinal physiological measurement data. This approach to clinical trial management promises to significantly change how trials are conducted and increase the value of trial data. However, the challenge lies in how to unlock the data’s value to make it more actionable, contextualized and meaningful. How will researchers turn the sheer volume of data they collect into quantifiable safety and efficacy measures and endpoints? At this point wearables don’t yet offer the type of medical or diagnostic-quality data that’s necessary for most clinical trials. Researchers must ensure not just accuracy of data, but also be able to evaluate and identify the data pertinent to the clinical trial outcome. For instance, a sleep monitor on its own cannot contextualize the reason why people wake up – they may be having an asthmatic attack, or a bad dream, or simply need the bathroom, but the monitor registers each of these instances as the same event. Or take the scenario of a trial participant who transfers his/her activity tracker to someone else – what would happen to the validity of the data in this case? How can researchers handle patient device use and adherence variability?

Stakeholders must work together to determine how to best deploy wearable devices to patients, define standard use, mitigate variability of use, link the data from these devices to traditional clinical data, account for data collection in a non-controlled environment, and maintain privacy and data security. With much work still to be done to scientifically evaluate the real impact of wearables on clinical trial data, regulatory compliance in collecting clinical data outside of a controlled research environment is an on-going challenge. Wearables offer an opportunity to disrupt the clinical trial process, leading to a radical redesign of patient-centered clinical trials.  For now, we must learn to balance the hype which surrounds wearable technology with the operational and design challenges posed by standardizing and controlling the data collected for use in clinical trials. Focusing on these challenges will help to ground wearable technology in the reality of what is achievable, while the industry takes its first steps on the path toward designing next-generation clinical trials through wearables, and ultimately new ground-breaking drugs and treatments.