Technology Enablers that Allow for Decentralized Clinical Trials | The Future of Clinical Data Management Series

This blog was authored by Amy Calvin, Senior Engagement Consultant, Strategic Consulting, Medidata.

The growth of decentralized clinical trials is being enabled by several key technologies that span the entire clinical trial spectrum. To ensure these technologies are deployed successfully, upfront strategies and planning are critical so that common pitfalls and challenges can be circumvented, and the trial has the best opportunity for success. 

This post explores some of the most important decentralized clinical trial technology enablers, and considerations that should be accounted for when planning a decentralized study.

Technology Enablers that Allow for Decentralized Clinical Trials

Patient-Facing Technologies

The patient experience is paramount to the overall success of any clinical trial. Providing the patient with choices related to accessing trial information, user-friendly training materials, video visits, and direct-to-patient study supplies, among other options, are all important when it comes to optimizing a patient’s clinical trial patient experience.

In addition to individual patient technology enablers, broader information sharing within digital communities is also possible with patient-centric technology platforms that facilitate processes, provide easy web access to necessary information, trial updates, alerts, etc. while allowing for patients to provide input and feedback on the trial. Collectively, these are all ways that patient-facing technologies can improve the patient experience, and as a result, increase study recruitment and retention.

Clinical Trial Protocol Development and Design Capabilities

Irrespective of the clinical trial design—decentralized or traditional—the protocol serves as the trial playbook. Broadly, it defines the study design, goals, objective, outcomes, and activities to ensure it can be completed safely. Technologies that allow for an understanding of site and patient burden during protocol development and design can help determine the appropriate level of ‘decentralization’ within a specific trial which increases its overall probability of success.

A question that is often asked is “How much decentralization is too much?” While there is no easy answer to this question, the amount of decentralization within a trial can be effectively managed by considering both the patient and site perspectives, including any possible concerns related to privacy. 

For example, wearable devices offer the ability to remotely capture clinical trial data in a very comprehensive manner, but introducing too many sensors for remote data capture can create unnecessary site and patient burden—ultimately impacting enrollment and retention. Therefore, finding the right balance is important.

Remote or Onsite Consent

Traditionally, patient consent has been a discrete event and not considered as an ongoing continuous process enabled by technology. Depending on the trial type, electronically capturing and automating the patient consent process provides flexibility and consistency of information exchange and data capture. Providing easy to understand information and the ability to access the consent throughout the trial is important, while of course ensuring the appropriate regulatory compliance is maintained in the process.

Outcome Data Capture

The internet of things has resulted in a plethora of consumer and medical grade technologies for remote data collection. Unfortunately, selecting the right tool is not always a straightforward decision. Prior to selecting a tool, the first step should be to clearly identify the digital measures of interest.

For example, if you are exploring whether or not a digital measure(s) could be used as a biomarker to understand efficacy, then mobile technologies that help to understand elements of improvement or decline (i.e., steps, sleep duration, etc.) should be taken into consideration. If continuous safety monitoring is required, introducing a sensor that generates digital data such as heart rate, temperature, etc. could be considered.

No matter what the end use of the digital technology might be, it is critical to define the rationale, purpose, and goals for inclusion of the tool since this process can help narrow down the choices for what tool might be best to use. In other words, this exercise is an important step in finding the right tool(s) for the job.

In addition to digital measures of interest and identifying sensors for inclusion, data interoperability, ingestion, and access are other critical technology considerations. Ultimately, a single data platform with a variety of available digital measures via various sensors is ideal. This allows for contemporaneous data collection in any environment, end-to-end data flow and access to unified data sources which results in faster, more robust clinical trial decision making.

Data Oversight

In a decentralized trial, data oversight and critical data sources may vary from the norm. For example, data sources may include electronic patient reported outcomes, a variety of sensors, and home health procedure results (e.g., labs).

Regardless of how/where data collection occurs, data platforms that allow for real-time/remote access of all clinical trial data collected is important so that automated and intelligent processes can be deployed to provide near real-time review of data. In addition, depending on data oversight strategies, the skill sets and roles of clinical data managers may look different than a traditional clinical trial. Defining strategy, roles, and responsibilities associated with data oversight of the decentralized trial are important first steps. Three areas for consideration as part of data management strategies are:

1. Real-time compliance monitoring to understand data completeness,
2. Data monitoring for safety, and
3. Data monitoring for data quality and completeness.

In addition, using risk-based quality management assessment tools can also be useful to define and identify critical data elements, key risk indicators (KRIs), quality tolerance limits (QTLs), and outlier processes associated with the task of monitoring data collection as part of a decentralized trial. 

Issue Management

Once key risk indicators and quality tolerance limits are defined, and the appropriate data oversight technology enabler(s) are in place, the ability to evaluate the clinical trial data becomes an event of real-time (versus episodic) monitoring. Using this approach, issues related to data anomalies, quality, and gaps can be identified in parallel and resolved in near real-time.

Thus, the need for technology enabler(s) that allow for a consistent process and capture of data associated with issue management and resolution is of utmost importance. This technology enabler allows for an increase in overall data quality, an efficient and effective process, and an automatic audit trail for transparency and awareness. 

Prior to embarking on a decentralized clinical trial, we highly recommend engaging in early discussions with experts in decentralized study designs and to take into consideration the technology enabler topics discussed above. Early planning, guided by a clear strategy and objectives, will provide the best possible chance of decentralized clinical trial success.

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