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Leveraging patient-centricity and decentralized trials to drive necessary innovation.
October 22, 2024
By: Kristin Brooks
Recent surveys suggest that as many as one-fifth to one-third of participants drop out of clinical studies.1, 2 Certainly, precarious patient health is a contributing factor to such poor retention, as is misalignment on inclusion criteria. But those aren’t the only barriers to patient retention. Quite simply, too many patients find it too difficult to participate in clinical trials. As healthcare technologists, we assume a heavy responsibility for making clinical trial participation less burdensome. That responsibility entails asking ourselves some difficult questions, such as: · How are we gaining access to a pool of potential participants? · How are we reaching out to them? · Once we’ve found that pool of patients, how do we elicit their interest and secure their engagement? · How do we facilitate data collection in an increasingly complex environment? · How do we ensure patients’ active, protocol-compliant participation throughout a study? A common thread running through those questions is the imperative that patients must perceive a benefit to participating in clinical trials, and that trials must serve patients’ interests, as opposed to solely serving sponsors’ interests. Hence our increasing focus on patient-centricity, a trend accelerated by the COVID-19 pandemic. Impact of the pandemic on patient enrollment and retention One positive outcome of the pandemic was the ascendance of patient-centricity as a guiding principle of clinical research and development programs. As vast pools of potential participants retreated to their homes and cut back on in-person visits, a host of technologies emerged to keep patients engaged in an intuitive manner while minimizing friction in their lives. However, despite those noble objectives, achievement of true patient-centricity has remained elusive, even with the pandemic largely behind us. Essentially, the pandemic artificially accelerated technology development but created gaps between new offerings and existing systems, resulting in numerous data silos that undermined patient-centricity. The emergence of decentralized clinical trials (DCTs) epitomized that conundrum. Fine-tuning the DCT model In a fully decentralized trial, the patient enrolls remotely and the sponsor (or CRO) sends monitoring equipment to the patient’s home; the sponsor/CRO also periodically sends lab technicians to the patient’s home to collect samples. However, most DCTs exist on a continuum between fully remote participation and the standard, in-person model. In a 2021 AbbVie survey, 82% of patient respondents expressed a preference to travel an hour or less to a trial site, and the same percentage said they were willing to remain on-site for two to four hours during an average visit in the first three months of the study.3 In practice, DCT enrollees mostly participate from home, where they make extensive use of sensors or devices that capture vital signs, lab values, and other key data. With many of these remote tools accessible via smartphone or tablet, it stands to reason that patients tend to prefer fully remote involvement, especially if they are immunocompromised, or if they have limited access to transportation. Indeed, in a recent McKinsey survey, up to 98% of patients reported satisfaction with telemedicine.4 Although the advent of DCTs was long considered inevitable, the pandemic accelerated demand for and adoption of the DCT model. However, much of the technology was not ready when the pandemic struck. Whereas a number of companies stepped into the breach to provide solutions, many of their products were not fully developed or vetted. Nevertheless, some of these companies were hailed as industry saviors. Faced with the imperative to keep their R&D programs on schedule, pharma and biotech companies had little choice but to partner with the so-called solution providers. The transition was not pretty. Many technology vendors offered costly solutions that took considerable time to get up and running. Moreover, many of those early products and platforms lacked standardized frameworks for getting data in or out. Even when they reached the point where they could collect data, vendors remained reliant on relatively primitive electronic data capture (EDC) platforms that often trapped data in a silo, leaving the sponsor in a quandary. As a trial ended, the data would remain inaccessible and unusable, ultimately losing value and undermining the overall results. Those early shortcomings forced many vendors to the wayside. The vendors that are still around are those that eventually found their footing and were able to break down the data silos in a cost-efficient manner. Although some customers were disillusioned by the early failures, many began demanding a hybrid solution that struck a balance between the standard and the fully remote trial models. The hybrid model has become increasingly attractive to industry because it allows for the retention of mature data-gathering systems and adapting them to make them more conducive to patients’ lifestyles and preferences. These systems rely upon EDC platforms that have been updated to facilitate collection of patient-reported outcomes (PROs); use of those platforms can reduce the burden of trial participation and help to improve retention, while also empowering patients to access meaningful data about their own health. Indeed, research suggests that deployment of smartphone-based ePRO solutions can improve compliance rates to north of 90%.5 Increasing the diversity of clinical trial populations Easing the burden of participation should make clinical trial populations more diverse. Yet despite recent FDA guidance encouraging racial and ethnic diversity in clinical trials6, there has been little progress towards this goal. That is largely due to the lack of robust and reliable data on race, ethnicity, and socioeconomic status on a global scale. Without adequate data to identify relevant population groups for a planned trial, inequities will remain unseen and unaddressed. Technology companies such as Anju are developing clinical and business intelligence tools that aggregate and connect data from multiple sources into a single intuitive database to optimize trial diversity. Anju’s TA Scan allows sponsors and CROs to visualize participants’ ethnicity, socioeconomic status, and site/primary investigator (PI) experience on a single map. The data can be intuitively filtered for age, gender, racial distribution, or average income, and can be visualized within the TA Scan application, exported from the tool for analysis, or alternatively delivered via the application programming interface (API). TA Scan can also streamline site selection by prioritizing sites based on their capacity to take on additional trials. The technology can thus save time and manual effort while ensuring a cohesive site selection and recruitment strategy. Keys to future success The limitations of the early EDC systems and the resulting data silos underscore the need for solutions that are more mature and deliver greater return on investment, with a higher likelihood of success. However, despite the strength of the broader economy, the pharma/biotech sector is combatting significant economic headwinds; for trial sponsors, money is the most expensive it has been for the past 20 years, from a lending perspective. Hence the need to do more with less, and to mitigate risk as much as possible. For sponsors aiming to improve patient enrollment and retention, success will hinge on the following imperatives: (1) Integrate data from multiple sources as easily as possible. It is crucial to ensure data are not stuck somewhere inaccessible. In the early 2010s, once the industry recognized how data silos increased costs and made it harder to complete trials, there was a push for unification. That push yielded greater acceptance of web services and APIs to automate data-gathering as much as possible. Now, as we emerge from the pandemic, a fully unified system may still be aspirational, based on the volume of data we are collecting. Nevertheless, the goal should be for systems that enable free-flowing integration of data from all available sources, allowing sponsors to look across every aspect of trial data. (2) Make patient access as easy as possible. Sponsors and CROs face the challenge of facilitating direct patient contact with mature solutions that enable patient access but aren’t so proprietary that they make it difficult to do business. Ideally, patients should be able to use a standard mobile app that is accessible via the internet and that doesn’t require purchasing a new device or provision of a device by the sponsor/CRO. Any app or device that patients are uncomfortable with may limit participation and inclusion. At the same time, devices need to be validated and approved by the FDA, and trial protocols should explicitly outline parameters for their use. (3) Facilitate use of validated sensor-driven data. To increase the volume of data that are captured and processed, sponsors must be confident that the data are valid and can be included and accepted in an FDA submission. As the use of sensors has increased and as sensor-based data have begun to traverse the regulatory submission gauntlet, various device selection criteria are becoming commonplace, helping to standardize this mechanism as a consistently dependable and viable option for the collection of valid data. The most important consideration, which is multi-layered in nature, is the need to differentiate between consumer- and medical-grade devices. That consideration often dovetails with data traceability, security, and privacy standards, which should not be overlooked if we are sincerely working toward patient-centricity.7 (4) Adhere to FDA guidances on DCTs8 and diversity in clinical trials.6 These guidances are designed to provide a measure of accountability for sponsors, investigators, and other stakeholders in ensuring the ethical and equitable conduct of clinical trials. Notably, the 2023 DCT guidance builds upon FDA recommendations issued in March 2020 to facilitate decentralization in response to the COVID-19 pandemic.9 To have updated those initial recommendations in such a short time frame is nothing short of light speed by FDA standards. More importantly, these guidances exemplify the Agency’s commitment to these principles, and the pace of updated recommendations is further evidence that the world of clinical trials is changing. References:
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