How Wearables Are Changing the Way We Collect Real-World Data in Clinical Trials

We can say with a fairly high degree of certainty that wearable technology will change how we collect real world data in clinical trials.
 
Traditionally, clinical trials rely on periodic visits to healthcare facilities, where data is collected through various tests, measurements, and patient-reported outcomes. However, wearable devices offer the ability to continuously and remotely monitor patients, providing a wealth of real-time data in their natural environments.
 
The strength of wearable devices is how they enable the collection of data out of sites and in the real-world setting. Therefore, a wearable device is fundamental to the way we collect real world data.
 
There are several benefits of using wearable technology to collect patient data in a real world setting such as:
 
1. Continuous Monitoring
Wearable devices such as smartwatches, fitness trackers, or patches can continuously monitor various physiological parameters like heart rate, blood pressure, sleep patterns, physical activity, and more. This allows researchers to gather a comprehensive dataset over an extended period, capturing the variability and trends that might go unnoticed during sporadic visits.
 
Due to the sheer increase in volume of data, data management teams must have a good understanding of how to handle, process and validate this amount of data. Also, biostatisticians are effectively spoilt for choice in the amount of data that can now analysis and this helps to improve the analysis of the investigational drug and draw significant statistical conclusions.
 
2. Objective Data Collection
Wearable devices provide objective measurements, reducing reliance on self-reported data, which can be prone to recall bias and inaccuracies. Objective data collected through wearables can enhance the accuracy and reliability of the information gathered during clinical trials. Although we are taking objective non bias data, this does raise concerns if the wearable device is capturing data accurately for us to be able to trust this data, especially since performing source data verification on wearables is more challenging.
 
3. Improved Patient Centricity
Wearable devices enable data collection without patients visiting sites and eliminates the need for frequent in-person visits. This reduces the burden of enrolling in a clinical trial and helps to increase patient recruitment rates and reduces patient dropout rates. This helps improve the volume and quality of data available for analysis, all while making it easier to have enough patients on a trial required to help hit sample size requirements based on the trial design.
 
4. Less Missing Data
Wearable devices can help engage patients actively in the trial. By providing real-time feedback, personalized recommendations, and reminders, wearables can motivate patients to adhere to treatment protocols, maintain healthy behaviors, and actively participate in their clinical trial.
 
Depending on the device, it can be actively collecting data required automatically so the patient needs to only keep the device on, but maybe the trial needs patients to perform certain activities at certain times. In this case, device notifications and reminders help with patient compliance and reduce missing data. Biostatisticians have methods such as Estimands for handling missing data, but reducing missing data in the first place is one of the best methods to resolve any issues it may cause.
 
5. Expanded Data Types
Wearable technology can capture a wide range of data beyond traditional clinical measurements. For example, wearables with sensors can detect gait abnormalities, tremors, or other movement-related information in patients with neurological conditions. This expanded dataset provides a more comprehensive understanding of patient health and treatment outcomes. It also allows for these data types to be captured in a more natural environment, for example, in a sleep trial, you are likely to get more natural and realistic data as patients are sleeping in the comfort of their own home, whereas sleep clinics may not generate as accurate data due to the unfamiliar settings.
 
6. Early Detection and Intervention
Continuous monitoring through wearables can help in early detection of adverse events or changes in patient health. Researchers can set up alerts or triggers to notify them when specific thresholds are crossed, enabling timely intervention and potentially preventing more severe health issues.
 
With advancements in wearable devices and the potential to transform data collection, improved data analytics, and appropriate study designs, wearable technology is likely to play a significant role in revolutionizing real-world data collection during clinical trials.
 
However, there are challenges such as data privacy, data accuracy, participant compliance, and the need for robust data analysis methods must be addressed.
 
One key challenge to explore is if a wearable device is fit for purpose and can be used on a clinical trial. In order to use a wearable, it needs to be adequately validated and the wearables themselves will undergo similar clinical trial analysis to ensure they can be used.

Trials to Validate Wearables

A trial to validate a wearable is like a medical device clinical trial. For example, if you wanted to use a wearable that measures blood pressure, a device trial would need to be conducted versus the already accepted blood pressure cuff, to demonstrate that the wearable is just as good (or good enough). Then, if that trial was successful the wearable could be used in a clinical trial of blood pressure medication to monitor the outcome.
 
Validating a wearable device for use in clinical trials typically involves conducting a separate trial specifically focused on assessing the device’s accuracy, reliability, usability, and safety. These validation trials, often referred to as “wearable validation studies” or “wearable feasibility studies,” aim to determine whether the wearable device can consistently and accurately measure the intended parameters in the target population. Here are some key aspects of such trials:
 
1. Study Design
The study design for wearable validation trials should be carefully planned. It typically involves recruiting a representative sample of the target population and comparing the measurements obtained from the wearable device with a reference standard or gold standard. The reference standard could be an established measurement technique, a clinical assessment, or another validated device.
 
2. Accuracy and Reliability
The validation trial assesses the accuracy and reliability of the wearable device’s measurements. This involves evaluating the device’s ability to measure the specific parameters of interest accurately and consistently, comparing the results to the reference standard. Statistical analyses, such as correlation coefficients, mean differences, or Bland-Altman plots, are commonly used to assess agreement between the wearable device and the reference standard.
 
3. Usability and User Experience
In addition to technical performance, wearable validation studies also assess usability and user experience. Participants’ feedback regarding the device’s comfort, ease of use, wearability, and acceptability is collected through surveys, interviews, or questionnaires. This information helps understand the practicality and user-friendliness of the device in the intended clinical trial setting.
 
4. Safety and Adverse Events
Wearable validation trials also evaluate the safety of the device. Researchers closely monitor participants for any adverse events or discomfort related to wearing the device. This information helps assess the device’s safety profile and potential risks associated with its use.
 
5. Data Handling and Integration
Validating a wearable device for use in clinical trials involves considering the device’s data handling capabilities and compatibility with existing data management systems. Researchers need to ensure that the data collected by the device can be effectively integrated into the trial’s data infrastructure for further analysis.
 
6. Regulatory Considerations
Depending on the intended use of the wearable device, regulatory bodies such as the U.S. Food and Drug Administration (FDA) or European Medicines Agency (EMA) may have specific requirements for validation and approval. Researchers need to ensure compliance with relevant regulations and standards to demonstrate the device’s safety and efficacy.
 
It’s important to note that wearable validation studies are specific to each device and its intended use. The trial design and validation process may differ based on factors such as the target population, parameters being measured, intended clinical application, and regulatory requirements. Collaborating with experts in clinical research, biomedical engineering, and regulatory affairs is crucial to design and conduct robust wearable validation trials that meet the necessary standards for clinical trial use.

Conclusion

In conclusion, wearables are great tools for capturing real world data and will enhance the clinical trial process and studies that they are used in. They aid in the use of decentralized trials and are growing in popularity, however for a wearable to be fit for purpose they must fit be validated themselves and approved on a wearable validation study. These studies will ensure the regulatory agencies are happy with the data accuracy and enable the virtual trial the uses the validated wearable to go ahead.
 

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Claude Price is the Head of Clinical Data Management at Quanticate.