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Mapping digital health transformation: from digital endpoints to device selection

From advanced sensors and artificial intelligence to big data and 5G networks, digital health technologies are creating new opportunities for biotechs and pharmaceutical companies. What’s more, as the general population becomes increasingly familiar with these technologies in their homes — not only to monitor their own health, but also to have better communication with healthcare providers via telemedicine visits — the remote monitoring aspect of these technologies can enable physicians to intervene based on real-time data.

Additionally, with regard to clinical trials, connected medical devices and wearables have facilitated the growth and adoption of digital endpoints, which are more responsive to change than traditional site-based outcome assessments. These endpoints are currently being used mostly as supplementary endpoints, having the potential to support patient outcomes at every stage of a patient’s clinical trial journey.

To maximise the value of incorporating digital endpoints into a clinical trial, sponsors will need to understand how to implement an end-to-end approach. At ICON, our framework maps the transition from device selection to digital endpoint validation, which leads to a better understanding of the operational excellence needed for managing data and mitigating risks.

Step 1: Adopt a patient-centred approach

Using a patient-centred framework that has evolved from proven clinical outcome assessment (COA) principles and techniques can help build the evidence required for submission to regulatory bodies. Previously, the industry has focused on the selection of devices for use in clinical trials, and not the endpoints. Today, however, sponsors must shift their attention to endpoints, particularly those that are meaningful to patients.

In some instances, endpoints may be focused on assessing improvement in everyday functioning, while in others, it will 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.

Step 2: Select the device

After identifying relevant, patient-centred endpoints, sponsors can next consider device selection, which includes device identification, patient acceptance testing, and technical usability and feasibility testing.

Sponsors will need to select the evidentiary requirements necessary to support device selection, including any gaps that need addressing. Collecting evidence could include using existing literature, developing a validation plan or using an industry-led endpoint qualification. COA instruments may be applied to help fill gaps and evidentiary needs.

Further, sponsors will have to consider how to collect and interpret data from the device and establish meaningful change thresholds for each novel digital endpoint.

Step 3: Adhere to operational excellence in digital endpoints

Operations are essential to ensure robust, accurate and compliant data collection. Overlooking operational excellence can jeopardise the endpoint.

Here, sponsors will need to consider the end-to-end process holistically and implement risk contingencies, including data management and compliance. For example, sponsors will need to decide how to manage missing data, whether random (e.g., patient takes device off in the shower) or not (e.g., patient takes device off because it is itchy), to ensure the data collected throughout the study remains usable.

Also, patients will need training on their devices and how data will be shared. As such, sponsors should set up patient support including direct outreach, reminder apps and dedicated help desks to keep patients compliant and engaged. Moreover sponsors should provide plans to capture and address non-compliance with regard to when, where and how often a device is worn and the loss or malfunction of a device. Lastly, sites and study staff should be trained on devices, and equipped and prepared with firewalls, ample storage and technology support.

The digital transformation is here

Digital health technologies provide new ways to gather data, while relieving stresses and burdens to patients. Clinical trial processes will become increasingly driven by large real-world data, interoperability and advanced computing power with the potential to accelerate drug approvals. As more digital technologies enter the market and become increasingly integrated into clinical research, we will begin to witness a shift from digital endpoints used as supplementary to primary endpoints. Moreover, sensor technology will advance, leading to a rise in clinical grade wearables, and increasing the quality and value of the data they provide, further spurring growth in the wearables market.

However, implementation brings new challenges, including patient acceptance, device suitability, data management complexity, and privacy and security issues. Having a strategic partner with wearables and COA expertise can help to mitigate risks and lead to the successful use of digital endpoints.

Learn more about our end-to-end approach for supporting wearables and digital endpoints in clinical trials in our white paper, Advancing digital endpoints: An end-to-end approach to managing wearable devices through clinical development.

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