Digital Medication Adherence enables Data-Guided Feedback and Patient-Centered Clinical Trials
Contributed commentary by Bernard Vrijens
June 17, 2021 | While medication adherence has long been a measure of engagement with treatment in the healthcare setting, the metric has not, so far, been translated into the sphere of clinical research. It is not hard to see why. Traditional measures of medicine-taking behaviour are not fit for purpose and the complexity of the problem makes successful intervention time- and resource-hungry.
As the industry continues its march towards patient centricity, however, things are changing. It is time to embrace the combined power of digital health, smart devices and packaging, and data science to finally understand medication adherence, and use that knowledge to support participation in clinical trials.
Why Patient Centric Trials?
The benefits of patient centric clinical trials are well documented and run the length of the development pathway. Involving the end users in candidate and target selection ensures developers are working to tackle true unmet need, and a focus on patient centricity can also help ease the age-old problem of poor recruitment and retention. What’s more, post-approval marketing teams can derive real benefit from having a better idea of how the product is used, received, and valued, in “the real world”.
But while organisations agree that patient centric trials can lead to better products and a higher return on investment, the industry is largely unsure how to go about making it happen.
Where Does Medication Adherence Fit In?
Adherence to study medications is a billion-dollar problem. Each Phase III trial participant is responsible for an average of $42,000 in costs, yet 30% are non-adherent by day 100. Non-adherence drains study power, can lead to inaccurate calculations of product efficacy, and can delay the approval at a cost of between $600,000 and $8million a day in lost revenues.
But rather than a problem to be solved, adherence is an opportunity to be embraced.
Medicine-taking patterns are a rich source of invaluable insights: poor adherence may be a sign of poor product efficacy, intolerable side effects, or administration problems, for example. And while adherence to medication is widely accepted as a marker of engagement within long-term condition management, its complexity means the concept is rarely translated to clinical trials.
It is a problem of two halves. Validated adherence measures are few and far between, non-standardised and imperfect. And when study teams are able to establish non-adherence, the reasons behind it are so multiple that interventions must be personalised to both the drug and the patient.
Digital health holds the solution. Study teams can now use remote monitoring and data science, to accurately measure adherence and rise above the one-size-fits-all approach.
Remote Adherence Monitoring
Remote adherence monitoring creates a closed feedback loop between the trial and its participants. It starts with smart drug devices and packaging, which records automatically dose administration and transmits that information to the study team. Connected pre-filled syringes, for example, collect essential information, such as if the injection has been administered, time and date, type of drug, batch number, and expiration date. In contrast to traditional, inaccurate, unvalidated measures, this approach works. Studies have shown that smart device and package monitoring is 97% accurate, compared to 60% for pill counting, 50% for healthcare professional rating, and just 27% for self-report.
Of course, collecting the data is only one part of the story. Remote adherence monitoring also uses data science to provide a complete picture of medication-taking behaviours and key indicators for risk stratification and prevention. Dosing history data, a series of time points corresponding to when the person accessed their package to administer their medication, is perfectly suited to data science—or the identification of patterns and causal relationships within large, complex datasets. Adherence analysts can apply powerful algorithms to this data to study individual medication intake behaviours, and how they change over time.
This digital approach can pinpoint potential trouble sites, as well as participants with possible adherence problems. It can also offer insights into the reasons behind these problems, by differentiating between people who forget take a morning dose and those who are taking a “therapeutic holiday”, for example.
Essentially, these data insights can guide questions during consultations, and inform personalised, patient-centred interventions. What’s more, participants can also access their own adherence data, through integrated patient-facing apps. Not only does this serve to reinforce engagement, it also helps people to develop strong medication-intake behaviours.
Ultimately, adherence-informed trials lead to optimised drug development. The benefits include improved agreement to the medication intake schedule, improved data quality and statistical power, and a reduced time to market.
Incorporating digital monitoring metrics and using them to encourage adherence can radically increase patient engagement in the protocol and boost the trials’ likelihood of success. Because the stronger the data behind a study, the better the outcome for pharma, clinicians, and patients alike.
Bernard Vrijens is CEO & Scientific Lead at AARDEX Group. He holds a PhD from the Department of Applied Mathematics and Informatics at Ghent University, Belgium. He currently leads a research program investigating (a) the most common errors in dosing using a simple but robust taxonomy, (b) particular dosing errors that can jeopardize the efficacy of a drug, and (c) the optimal measurement-guided medication management program that can enhance adherence to medications and maintain long-term persistence. Dr. Vrijens is also the co-author of seven book chapters, over 100 peer-reviewed scientific papers, and named as inventor on 6 patents. He is a founding member of the International Society for Medication Adherence (ESPACOMP), and an active member of several EU- and US-funded collaborative projects around the theme of adherence to medications. He can be reached at email@example.com