Planning Ahead: 5 Best Practices For The Integration of Wearables in Clinical Trials
Written by Christine Guo, PhD |
Wearable, sensor-based digital health technologies (DHTs) can help biotech and pharma teams accelerate their clinical development programs with continuous, objective, real-world data collection. This type of comprehensive data from DHTs can provide unique insights on patient functioning to support decision making and even complete studies with fewer participants. DHTs also support patient centricity by enabling measures that are meaningful to patients’ quality of life, and remote data capture helps to reduce participant burden. Spurred in part by the rise in decentralized trials in recent years, the momentum behind DHT adoption has grown sufficiently that both the FDA and EMA have released guidance related to their use in clinical trials.
When considering integrating wearable-derived metrics into clinical trials, sponsors must prioritize several key considerations to fully realize the benefits that DHTs could bring to their specific trial. Planning ahead will allow your team to
- optimize the utility of wearable data,
- safeguard data integrity, and
- foster productive interactions with payers and regulatory bodies.
Here are 5 key considerations to help you plan ahead and maximize the value of integrating wearables into your clinical development program.
1. Plan for evidence generation ahead of time
You will want to devise a clear strategy for incorporating wearable data into your clinical programs. Initially testing wearables in isolated pilot studies isn’t a bad idea, but doing so without establishing a long-term strategy is a bad idea. This can potentially lead to inadequate data collection and analysis, therefore reducing the potential insights you’ll be able to draw from a sufficient wearable data set.
To secure a regulatory endorsement, program leaders should proactively devise evidence generation plans and strategically deploy DHTs in early-phase trials. This is particularly relevant if you work for a large company managing multiple assets within the same indication - shaping the strategy around the indication or therapeutic area is recommended over focusing solely on individual assets.
2. Prioritize data and platform stability
Clinical development can span multiple years, necessitating sustained data integrity and consistency. For the technology industry, renowned for its agility and rapid evolution, this environment can be challenging because significant technological changes during a trial or between early and later phases can jeopardize its integrity.
According to the FDA’s recent guidance on DHTs, clinical trial sponsors are mandated to assess all updates to DHT platforms to ensure compliance with regulatory standards. Therefore, you should look to platforms that emphasize stability and backward compatibility over frequent updates - even if it means delaying the adoption of the latest technology.
3. Retain raw data as source data
Raw data from wearables is collected at high frequency, generating multiple data points per second. Preserving this raw data is essential to maximize value throughout your clinical development programs and beyond. Digital clinical measures (such as total sleep time, gait speed, or step count) are generated from raw data using various algorithms. Similar to individual item scores for patient-reported outcomes (PROs) or clinician-reported outcomes (ClinROs), the algorithms used for wearable data are intricate and significantly impact the accuracy and reliability of the resulting digital measures. Algorithm development is a dynamic area of research within digital health science, continually evolving alongside rapid advancements in data science.
Retaining raw sensor data allows your team to embrace novel health metrics while ensuring compliance with regulatory requirements for data integrity. Further, sensor data from wearable devices is captured continuously for days, weeks, months, or longer. This volume of high-quality data about participant behavior is a valuable resource for using powerful AI tools that can help advance clinical research.
4. Focus on a tailored statistical approach
Paying attention to the statistical analysis of wearable data is crucial. Your team must assess the resources and methodologies required for analyzing this unique data type, which differs substantially from the discrete data points typically associated with traditional endpoints. Due to its unique nature, special consideration and innovative approaches are necessary for analyzing wearable data.
Wearable DHTs are often included in trials as exploratory endpoints, which can lead to them being underutilized especially if the bandwidth and familiarity with DHTs within the biostatistics team is limited. Proactive resource allocation, tailored analysis approaches and collaboration with specialized technology vendors can address this issue to make sure your team is getting the most out of wearable data and not leaving any insights uncovered.
5. Participate in industry collaboration
Industry collaboration is essential for overcoming evidence gaps and advancing new digital measurements as validated clinical endpoints. DHT solution providers and sponsors are pooling their multidisciplinary expertise to decipher the complexities of wearable sensor data analytics and correlate them with clinically meaningful outcomes. The goal of this collaborative effort is to integrate wearables into mainstream clinical development practices. Pre-competitive working groups are emerging to develop tailored DHT solutions and streamline operational and regulatory hurdles.
For example, the DECODE Nocturnal Scratch working group, involving several global pharmaceutical sponsors, aims to develop a fit-for-purpose DHT tool for measuring nocturnal scratch in atopic dermatitis. Once established, this will be a promising candidate for significant regulatory endorsement by health authorities and tool to advance evidence accumulation.
By now, you must be thinking about how prepared you are to integrate wearables into your clinical development program, but we couldn’t let you go without one more key consideration -
Bonus #6. Don’t overlook the needs of sites
Clinical trial sites play a vital role in the integration and successful deployment of wearable devices. Incorporating wearable technologies into protocols introduces new complexities for sites to manage, including ensuring seamless device use aligned with site appointments, addressing patient concerns regarding device use and integrating wearable data into clinical workflows. Sites must also navigate regulatory requirements and operational logistics associated with wearable deployment. Functional partnerships between sponsors, technology providers and clinical sites are essential for overcoming these challenges. Establishing collaborative efforts before the study can help to make wearable integration smooth and effective, such as working with technology providers to deliver comprehensive training and support for site staff and establishing clear communication channels for troubleshooting and feedback.
The drug development sector’s inherent risk aversion often acts as a barrier to embracing novel endpoints in clinical trials, leading to a cautious approach to adopting new technologies like DHTs. However, growing evidence and technological advancements have supported the value that integration of wearable DHTs can bring to clinical trial efficiency and effectiveness. With a little advanced planning, your team can capitalize on the promise of wearable DHTs to transform data collection and progress patient-centric clinical trials.