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Best practices for designing digital endpoints for COVID-19 clinical trials amid uncertainty

As pharmaceutical and biotech companies ramp up clinical trials for solutions to the COVID-19 pandemic, many have felt growing pressures to quickly identify effective treatments and vaccines to prevent the continued spread of the virus. With more than 700 drugs, from discovery through pivotal programmes, linked to COVID-19 and 2,000 clinical trials underway globally,1 sponsors will need to ensure that this sprint to find answers doesn't come at a cost - such as overhyped data, trials too small to yield answers, and poorly designed studies. More importantly, pharmaceutical and biotech companies conducting these studies will need to capture efficacy data, such as respiratory symptoms and laboratory testing for viral infection.

One way to improve not only efficacy, but also efficiency is to employ digital endpoints, which are generated and assessed using data captured from sensors, wearables and other digital health technologies, such as ingestible devices and implantables. Utilising data from these sensors can provide critical information on symptoms and identify digital biomarkers in real-time,  which are reported through analytics, often powered by AI. What’s more, this method of data collection can provide rapid, scalable and objective measurements.2 

The use of a digital device such an oximeter, for example, could monitor respiration rate changes in patients with COVID-19 infection during and after being treated with an investigational product (IP). In this example, collecting continuous data could indicate adverse events to the IP or provide more information on a therapy’s effects on respiration during and after treatment. Collecting this additional data and using them as endpoints can accelerate programme development and regulatory approval.

When designing trials to include digital endpoints, digital health technologies will need to be developed with users and their unique needs in mind. A product that is not useful to, or usable by, a patient will not be effective — no matter how great the product is otherwise. In addition, a product that does not integrate into physician workflows or demonstrate better patient outcomes, should not be used. To incorporate digital endpoints into a clinical trial, sponsors will need to understand how to implement an end-to-end approach using the following three best practices: (1) prioritising the patient, (2) selecting the device and (3) implementing operational excellence.

Prioritising the patient

Historically, the biotech and pharma industries have focused on the selection of devices for use in clinical trials, and not the endpoints. For success, sponsors need to take a patient-centred approach when considering study objectives. Instead of asking how to use digital devices in a clinical trial, sponsors should ask why are digital devices being used. Just because digital devices can be applied to clinical trials, does not mean they should be incorporated.

In some instances, endpoints may be focused on assessing improvement in everyday functioning, while in others, it may be about measuring stability or deterioration in a condition - how quickly and by how much. Once sponsors understand which outcomes are meaningful to patients, they then can begin to identify and select the optimal measures to assess these endpoints.

Selecting the device

After identifying meaningful endpoints to patients, sponsors can consider device selection, which includes device identification, patient acceptance testing, technical usability and feasibility testing. One approach, recommended from the ePRO consortium,3 includes the following evidence to support digital endpoints:

  • Content validity
  • Reliability of the endpoint (using statistics such as the intraclass correlation coefficient, which gauges the reliability of measurements or ratings)
  • Criterion validity (which validates the endpoint against a gold standard)
  • Ability to detect change in an endpoint

Regardless of the source, clinically meaningful endpoints need to directly measure how a patient feels, functions or survives. It is also important to think ahead to the interpretation of the data that the device provides in a study - for example, establishing meaningful change thresholds for each novel digital endpoint. Meeting with a clinical outcomes assessment expert early on can help you select the evidentiary requirements needed to support device selection, including where there are gaps that need to be addressed.

Implementing operational excellence

To ensure robust data collection, it is essential to consider operational excellence. This is critical because, if overlooked, digital endpoints can be severely jeopardised. When considering the end-to-end process holistically, sponsors will need to implement risk contingency, including logistics, data management, and patient and site compliance. Further, for data management, sponsors will need to determine how data will be aggregated, processed and cleaned, in addition to deciding what constitutes a valid data set and how to manage missing data.

Also, patients and study staff will need training on their devices and how data will be shared. Lastly, sites should be well equipped and prepared with firewalls, ample storage and technology support.

Adopting a strategic digital endpoint framework

Novel digital endpoints in COVID-19-specific studies — whether for drugs or vaccines — can prevent the premature termination of promising products, due to a lack of evidence, by measuring concepts that could not have been previously assessed or were measured inadequately. Harnessing digital endpoints in clinical research can improve our understanding of the safety and efficacy profile of a product, which may lead to greater success from discovery to commercialisation.

Effective integration of digital devices into trial design, execution and reporting requires a strategic end-to-end approach. At ICON, combining digital health technology expertise with patient-centred scientists, we have developed a framework to map the process from device selection to endpoint validation. For more information on using digital endpoints in clinical research, read our latest white paper: Advancing digital endpoints: An end-to-end approach to managing wearable devices through clinical development.

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References:

Carroll, John. Covid-19 has roiled clinical trial plans around the world, raising concerns over the industry’s future on new drug approvals. (July 2020). Endpoints News.

Taylor, Nick Paul. BARDA backs push for clinical-grade wearable to detect signs of COVID-19. (July 2020). MedTechDive.

Byrom, B., Watson, C., et al. (2018). Selection of and Evidentiary Considerations for Wearable Devices and Their Measurements for Use in Regulatory Decision Making: Recommendations from the ePRO Consortium. Value in Health. 21:6, 631-639. https://doi.org/10.1016/j.jval.2017.09.012.

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