Decentralized trial model pushing research to ‘new standard’: AiCure

By Jenni Spinner

- Last updated on GMT

(Vitaliia Hryshchenko/iStock via Getty Images Plus)
(Vitaliia Hryshchenko/iStock via Getty Images Plus)

Related tags AiCure Decentralized trials patient engagement Remote patient monitoring Artificial intelligence COVID-19

A leader from the trial tech firm says COVID-19 has accelerated virtual studies, creating opportunities to improve patient engagement, costs and data.

Thanks to the global pandemic, clinical research stands at a crossroads. The surge in adoption of decentralized and hybrid trial models has sites and sponsors asking how the landscape will look in the coming months and years, and how can industry professionals make better use of decentralized trials and digital technology to improve results.

Outsourcing-Pharma spoke with AiCure’s chief medical officer, Rich Christie, about the evolution and increased use of decentralized trials, the advantages of this approach, and how to harness high-tech solutions like AI and remote monitoring platforms to optimize outcomes.

OSP: Could you please talk about how the industry’s use and acceptance of decentralized clinical trials had evolved in the months/years leading up to the pandemic?

RC: Over the last ten years or so, the industry has gradually realized the benefit of deploying technology that can help streamline various aspects of a trial. This includes virtual enrollment and electronic consenting solutions, as well as monitoring solutions that improve visibility into a patient’s wellbeing in between in-person visits, such as their dosing behavior or subtle symptoms that could be missed during periodic clinical evaluations.

By augmenting the role of brick-and-mortar clinics, these solutions have demonstrated their ability to make trials cheaper and faster, improve convenience, reach more patients, and enhance the integrity of complete, accurate trial data.

OSP: What are some of the ways the industry has changed since the arrival of COVID-19? Please feel free to talk about how the industry changed in the earlier part of the pandemic, as well as how they’ve adapted since.

RC: As was the case for many other aspects of healthcare, the pandemic accelerated the adoption of these technologies to ensure trial and business continuity. Because the pandemic reduced the willingness and ability of patients to visit clinics, many sponsors and study teams needed to modernize the way they reach patients; this resulted in a surge in the adoption of remote solutions to recruit patients for a new trial, engage with participants in an ongoing trial, and aggregate and analyze trial data.

Greater adoption means more advancements and possibilities, turning virtual trials into a new standard of clinical research.

OSP: What kinds of technology solutions have emerged and increased? How are these helping site teams continue their work, keep patient burdens low and engagement higher, and accurately collect data?

RC: Some of the best tools utilize devices that most patients are already familiar with, such as smartphones or tablets. We’ve seen studies leverage these tools to maintain constant communication with participants, monitor one’s compliance to a treatment protocol, and capture digital biomarkers and other sensitive data – all from the safety and comfort of a patient’s home. Not only are these technologies helping sponsors to keep their studies running, but they’re also providing not-before-seen visibility into patient behavior.

While this ability to activate a stream of real-time data has helped study teams maintain data integrity and quality during the pandemic, as virtual clinical trials continue to make their mark on the industry, we are at a pivotal moment in defining their role in the future of clinical research.

OSP: You mention you feel we’re at a “pivotal” moment in clinical research, where trial pros are determining the industry’s future. Could you please elaborate?

Rich Christie, chief medical officer, AiCure

RC: Because virtual trials are growing in popularity, many organizations are exploring whether visits to physical brick-and-mortar clinics are even needed and evaluating the potential cost savings with reducing their role. While the concept of a “siteless” trial may seem attractive, it fails to consider just how difficult and critical patient engagement is to a study’s success.

Cutting costs and improving convenience should never be the primary goals of any study. Instead, it should be to conduct the highest quality trial to create the highest quality drug that is based on meaningful, complete data.

Despite the explosion of innovation we’ve seen in the last decade and growth of AI-assisted technologies that allow us to collect data around the clock from patients wherever they are, the role of study teams remains crucial to collecting the best possible data. When you lose the patient-provider relationship, the patient’s engagement in the trial, and consequently the trial and the quality of its data, suffers.

The industry is at a pivotal moment in not only safeguarding the essential role sites play but also consolidating learnings from the use of new technologies and their ability to offer personalized support during the pandemic long-term.

OSP: How, with trials increasingly virtual or hybrid, can trials effectively manage their patient engagement strategy—what are some key concerns, and effective solutions?

RC: When discussing virtual trials, an often overlooked but critical component for study success are the clinical trial sites. While technology has certainly come a long way, the relationships between patients and their site-based caregivers remain critical and the challenges of executing truly “siteless” trials are becoming apparent.

Instead, virtual technologies, such as digital biomarkers and dosing support, should be used to complement the work being done by study sites and to help them do that work more efficiently. Receiving real-time data on changes to symptomatology means that study teams remain informed throughout the times between patient visits, whether in person or via video chat. With this amount of data at their fingertips, study team clinicians do not have to spend the majority of these visits recording data.

The digital biomarker and adherence data allow clinicians to focus their attention and support where it is needed during these important interpersonal interactions. This not only improves the patient experience but also keeps sites as the hub of a trial, an important piece of the puzzle.

OSP: How can advanced data tech like AI help with various aspects of decentralized trials?

RC: Companies engaged in virtual trials can benefit from remote engagement and monitoring technologies throughout the trial’s duration, but especially before it even starts. Optimizing the patient pool before the study begins can have a significant impact on the integrity and quality of study data.

As many as 50% of patients don’t take their medications as instructed and acceptable patient dropout rates of approximately 20% lead sponsors to enroll higher numbers in order to increase their chances of meeting study endpoints. By employing predictive dosing algorithms to evaluate potential study participants during a lead-in period, sponsors can use artificial intelligence tools to predict which patients will be most likely to perform well over the course of the study.

Dosing support technology can remind patients when they need to take their medication, and record each dose using the video capabilities of the patient’s smart device. Artificial intelligence within the application then analyzes the video and provides highly accurate dosing confirmations to the study team. The team can then create models based on this data to predict which patients will be most engaged during the study.

This kind of solution identifies the probable high performers, allowing sponsors to enroll the smallest number of patients necessary to produce the data needed to reach safety and efficacy endpoints. Since smaller trials often mean faster trials, patient pool optimization can be a significant cost-saver and can play a critical role in ensuring a virtual trial runs as smoothly as possible.

Once the patient pool is set, technology can be utilized to optimize their engagement and measure their response to a drug. This includes using computer vision models to guide and confirm a patient’s dosing behavior, leveraging digital biomarkers and ePRO to capture a patient’s symptoms, and engaging with patients virtually via telehealth to give them any support they need.

OSP: Could you please explain digital biomarkers, how they are used, and how they can benefit teams running decentralized trials?

RC: Digital biomarkers use technology to measure patient data that would be difficult or even impossible for human observers alone. This technology typically records patient behaviors via video and audio technology such as one’s smartphone, quantifies behavioral characteristics such as facial, vocal, and motor behavior, and derives clinically meaningful biomarkers to measure patient responses to treatment.

A patient can engage with their study clinicians via their smart device or record themselves performing a planned series of actions. The algorithms then work to identify changes in visual and audible characteristics that may indicate how the treatment is working.

If a patient’s symptomatology includes things like tremors, alterations in facial or vocal effect, or facial paralysis, any changes (positive or negative) will be logged in real-time, providing the study team with around-the-clock access to the data while also flagging them if intervention is necessary. This is particularly useful for the early detection of potential adverse events.

One key to the evolution of virtual trials will be the extent to which these proprietary solutions adopt open-science frameworks that encourage scientific scrutiny and collaboration. Scientifically validated digital biomarkers hold great promise to enhance a clinical trial’s objectivity, sensitivity, and frequency of assessment.

Despite this potential, this method of measuring patient behavior is often shrouded in mystery, as proprietary machine learning models are typically not accessible to scientists to independently evaluate. By breaking down these barriers and expanding access to these emerging approaches to remote patient assessment, we advance their development and their validity, deepen the pool of clinical data available to interpret study findings, and better equip sites to offer each patient the support they need.

OSP: Could you please talk about how site burdens change when trial teams move from onsite to decentralized, and how solutions like digital biomarkers can help manage site burdens?

RC: With most clinical trials, in-person visits are spread out weeks and sometimes months apart, and understanding how patients are feeling in-between visits has always been a concern for study teams. With technology like digital biomarkers, clinicians no longer need to solely rely on what they can glean from intermittent clinical visits. This enables them to use those face-to-face visits to focus on building a personal relationship with the patient instead of interviewing them and collecting granular trial data.

Patients that might need more support and oversight can have more time with their provider, and work together to remove any challenges they may be experiencing. Conversely, patients that have been extremely compliant can get in and out, and don’t feel like they’re wasting their time answering questions that the study team should already know the answers to.

OSP: Is there anything else you’d like to share with our readers that we didn’t touch upon?

RC: For sponsors seeking to launch virtual trials, or to get the most out of hybrid trials that employ a combination of traditional and virtual approaches, remote patient engagement and monitoring technologies can offer numerous benefits. Optimized patient pools, democratizing access to proprietary algorithms that provide key patient insights, and better-informed study teams can help sponsors run smarter, faster, and more cost-efficient clinical trials.

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