• Sven Jungmann

How to contribute to the digital transformation of clinical trials

An overview for digital health entrepreneurs

Digital innovation will transform clinical trials. It’s inevitable…still, innovators need to understand the why and how, so they can not only accelerate this needed transformation but find opportunities within a changing landscape.

The purpose of a clinical trial is to evaluate the safety and efficacy of new medical treatments, drugs, and medical devices. Digital technologies could improve the clinical trial process in the following ways:

  • Lower costs

  • Reduce the burden on patients and staff

  • Speed and/or automate processes

  • Reach larger and more diverse populations

  • Provide safer and more comprehensive reporting

  • Enable more endpoints through easier follow-up

When leveraging digital technologies, we gain the opportunity to solve or reduce the current operational inefficiencies in clinical trials that delay already-slow timelines, inflate costs, and hinder participant identification, engagement, and retention. To stop the vicious cycle that emerges when slow timelines and low participation interact with each other, the MedTech and Pharma industries are looking and paying for better and more cost-effective solutions.

Digital technologies can lend their three greatest strengths to these problems: streamlining costs, better data interactions, and providing a patient-centered experience.

Let’s see how these strengths could apply to a clinical trial setting.

Imagine this: A fully digital clinical trial

Participants are able to engage in clinical trials regardless of location, budget, or time constraints due to digital communication platforms and remote monitoring tools. This facilitates a larger, more diverse pool of potential participants, creating more comprehensive results and including previously underrepresented populations.

Once participants are chosen, digital interfaces help patients fully understand the process, timeline, and requirements and lead them through a transparent informed consent procedure.

After the study begins, data storage and analysis tools help collect, compile, and organize data around investigation endpoints, saving time and efforts for both researchers and participants through automation. Additionally, digital tools continuously accumulate information over extended periods of time, building on the traditional “only while in the clinic” data collection and identifying variances more comprehensively and/or adverse health events faster (which improves safety).

The result? Enhanced investigation results on the same or smaller budgets.

Specific examples of where digital solutions can step in

  • Recruitment: Digital solutions could help identify viable participants. One particularly interesting concept, a solution could automatically inform users (based on their data) about upcoming trials for new drugs or therapies that hold the potential to improve their health conditions. This service would be charged to the Pharma clients holding the clinical trials, but rather than selling user data, the solution developer would notify users privately of the opportunities and allow the users themselves to follow up if interested.

  • Retention: Currently, the lengthy trial process and undue burden on participation put a strain on retention. Digital communication solutions could provide easier conversation channels between researchers and patients as well as facilitate more cost-effective options for “visits” (i.e., video calls).

  • Informed consent: One main challenge of recruitment and retention has to do with informed consent. Trial language can be confusing, and researchers may not have sufficient time to fully explain all details and requirements of the study to each individual participant. Lower comprehension of these details leads to participant engagement problems which threatens the success and quality of the study. The use of video guides for patients to aid informed consent or AI solutions to translate trial requirements into common language could improve this process and help potential participating practitioners and patients find trials more easily.

  • Better data collection and storage: Today, most data collection for clinical trials is done manually. As an alternative, digital solutions could prompt data collection and storage both during visits and outside of them (real-world data), making this task more efficient and more thorough. This real-world data (RWD) could include demographics, activity tracking, digital biomarkers, patient-reported outcome, EHRs, and images or even biological samples taken at home. In addition, other study tasks could be automated by digital technologies; for example, participants could execute cognitive tasks on their smartphones to quantify the severity of Parkinson's Disease (Zhan, et al.).

  • Improving safety: By using remote monitoring tools and RWD, clinical trials could become not only more holistic but safer. Through these tools, the normal day-to-day in addition to clinic visits could be observed. This continuous approach helps account for variances not seen during visits and could recognize dangerous health instances more quickly.

Connecting the dots: RWD and Advanced Analytics

As digital tools improve and expand, so can their roles in clinical trial infrastructure. The key to this is reliable interoperability of high-quality real-world data. Already, several apps are working to connect EHR data across platforms, so that researchers, patients, and providers have access and so that health apps and medical devices can connect and integrate. This means that mobile devices, sensors (digital biomarkers, remote monitoring, activity trackers, etc.), and other patient-generated data could be included or serve as trial markers and endpoints. The SMART/HL7 Flat FHIR/Bulk Data Export API, for example, could potentially use EHRs to create population-level datasets.

In addition to automation connecting data, advanced analytic methods empowered by artificial intelligence (AI) and machine learning (ML) could enhance several areas of clinical trials:

  • Matching participants to clinical trials

  • Improving extraction of digital data

  • Helping interpret clinical trial findings

  • Analyzing EHR data to predict disease development (AKA computational phenotyping)

The biggest hurdle: Proving safety

The biggest challenge for innovators to overcome is validating digital solutions and tools for reliability, efficacy, and safety. This is a new sort of challenge that involves evaluating and properly utilizing real-world data to generate real-world evidence. To dive into this topic further, check out Is your real-world evidence (RWE) good enough? and How to use your real-world data (RWD) for clinical studies.

Final thoughts

Despite the slow adoption of digital alternatives in clinical trials thus far, we currently have the tools to transform clinical study design and function. From personal sensors to more accessible health records to telehealth options, innovators (whether in the research or patient care sphere) can contribute massively to the future of clinical evidence, which is not only socially important, but financially intriguing.

Source material: https://www.nature.com/articles/s41746-020-0302-y

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