Adherence monitoring can minimize variability and maximize engagement in DCTs
Decentralized clinical trials (DCT) are growing in popularity, thanks to their ability to tear down many of the long-standing barriers to robust medical research. And while this new model has some challenges of its own, focusing on adherence can help tackle them head-on.
COVID-19 accelerated the use of DCTs, but, in truth, the clinical research community had been on this trajectory for some time.
There is a growing acknowledgment that the model, which replaces at least a portion of on-site visits with remote monitoring, comes with a host of benefits.
It can, for example, help improve recruitment and retention, an issue the industry has been trying to get to grips with for some time. Some analysts estimate that as many as 50% of studies1 are delayed because they fail to recruit enough participants in the allotted time. And even when researchers have enough participants to start testing, around 30% drop out.2
By reducing the inconvenience and burden associated with frequent travel to clinic appointments, DCTs are more patient-centric than their traditional, on-site counterparts, which can boost recruitment and retention.
In addition, DCTs expand the geographical area from which researchers can draw participants. This is increasingly important in the personalized medicine era, where eligibility criteria can be as limiting as a single genetic mutation.
Crucially, this new model is helping to manage the growing complexity, duration, and cost of clinical development. Latest estimates put the cost of developing and bringing a new drug to market, for example, at between $314 million to $2.8 billion,3 but decentralizing the process streamlines it.
It enables teams to collect more data points, at times that are more reflective of real-world situations. What’s more, it makes that information easily accessible to researchers, allowing them to make informed, key decisions around things like dosing regimens.
New Model, New Challenges
There is no doubt that DCTs will play a major role in clinical research, but we must understand that this new model comes with new challenges: namely engagement and variability.
The industry needs to consider how it will ensure participants are engaged with the trial protocol with fewer face-to-face interactions to reinforce relationships and behaviors.
This begins at the start. Widening the pool of eligible candidates means recruiting people who may not necessarily have participated in trials before. Of course, expanding access increases inclusivity and helps provide a more representative patient population for drug testing – but it also means teams need to put more time, effort, and resources into onboarding research-naïve participants.
Researchers, then, need to establish engagement through truly informed consent at the start of the process and then maintain it throughout.
DCTs also challenge existing variability limits. Currently, we seek to limit the variability between participants through a range of measures, including inclusion/exclusion criteria, standardizing assessment procedures, selecting the “best” patients by site, and preferring hard outcomes over self-assessment.
With the direct-to-patient approach of DCT, however, will inevitably experience an increase in variability between and within patients.
There are two ways to approach this: recruiting the unrealistically large sample sizes that will be needed to show a meaningful effect despite variability or focusing on managing the key sources of that variability.
Medication Adherence is a Key Metric for Decentralized Clinical Trials (DCT)
Tracking medication adherence can help manage both engagement and variability, enabling research teams to realize the potential of DCTs.
Poor medication adherence, which affects around 50% of all clinical trial participants,4 is one of the most important sources of variability in clinical outcomes within a clinical trial.
It can lead to underestimations of drug efficacy, even to the point of study failure, underestimated incidence of adverse effects, and/or overestimated dosing requirements for marketed products. Adherence to the allocated trial intervention is fundamental for sound interpretation of ITT analysis and ensuring data quality, making it a key consideration in DCTs.
In terms of engagement, monitoring medication adherence can act as a barometer to how invested participants are in the study.
Non-adherence can be a dropout warning sign. It offers clues on poor product efficacy, intolerable side effects, or administration problems, all of which researchers need to know about, and all of which can result in poor retention.
Measuring medicine-taking behaviour has not always been easy. Traditional validated measures are few and far between, and those that do exist are non-standardized and imperfect.
Of course, establishing a problem is only half the battle. The reasons for poor adherence are complex, multiple, and individual, meaning successful interventions are personalized.
Digital adherence monitoring can help. It combines connected packaging and powerful analytics to measure, and help site teams manage, medication adherence.
Rather than relying on biased, subjective methods, such as pill count or self-report, it provides the objective, robust information that site teams need to spot people who might need additional support.
DCTs do not, and should not, mean leaving participants to their own devices. People still need “the human touch”, and this approach enables teams to offer remote monitoring while still providing personal contact when needed.
How does it work?
connected drug packaging records dose administration and transmits that information to the study team for analysis.
Connected blister packs, for example, can collect essential information, such as if the product has been removed from the packet, time and date, type of drug, batch number, and expiration date.
This information is then sent to a cloud-based platform that provides a sophisticated analysis of medication-taking behaviors and creates powerful visualization and focused feedback for both study teams and participants.
Crucially, we know that it works: studies have shown that connected package monitoring is 97% accurate, compared to 60% for pill counting, 50% for healthcare professional rating, and just 27% for self-report.5
The Future of Decentralized Clinical Trials (DCTs)
Thanks to their wide range of benefits, DCTs are fast becoming the norm in the clinical research space.
If the sector is to embed this more efficient, patient-centric model into its routine workflows, it must consider how it will minimize variability and maximize engagement. Medication adherence monitoring is the key to both.
- What challenges still face clinical trial recruitment and retention? (2020). http://www.pmlive.com/pmhub/clinical_research/couch_integrated_marketing/white_papers_and_resources/what_challenges_still_face_clinical_trial_recruitment_and_retention
- Alexander W. The Uphill Path to Successful Clinical Trials: Keeping Patients Enrolled. (2013). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3684189/
- Wouters O, KcKee M, et al. Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018. (2020). https://jamanetwork.com/journals/jama/article-abstract/2762311
- Eliasson L, Clifford S, et al. How the EMERGE guideline on medication adherence can improve the quality of clinical trials. (2020). https://bpspubs.onlinelibrary.wiley.com/doi/full/10.1111/bcp.14240
- Alili M, Vrijens B, et al. A scoping review of studies comparing the medication event monitoring system (MEMS) with alternative methods for measuring medication adherence. (2016). https://pubmed.ncbi.nlm.nih.gov/27005306/