Drug trials don’t succeed if the patient participants aren’t able to stick to the proscribed medication plan. Outsourcing-Pharma spoke to Bernard Vrijens, CEO and scientific lead of AARDEX Group, about how data analytic technology and techniques can be employed to help trial teams improve medication adherence, and about an interesting initiative the company is taking on to encourage better adherence.
OSP: Please tell us some of the challenges trials typically face around patient behavior—medication adherence, problems recording vitals, missed check-ins or telemedicine appointments, etc.
BV: Non-adherence to medication is a long-standing problem in clinical trials. Studies have shown that 30% of Phase III clinical trial participants are non-adherent by day 100. Across all clinical trial phases, 50% of participants admit to not following the dosing regimen set out in the protocol. This unmanaged non-adherence to study medication leads to distorted inferences about the drug’s efficacy and safety. It is challenging for clinical trial conduct.
By decreasing effect size and increasing variability, poor medication adherence drains study power. The exponential relationship between nonadherence and sample size means that any decrease in adherence must be met with an expensive increase in study participants to maintain power and avoid study failure.
The issue can also have a concerning impact on patient safety. It generates poor data, leading to improper calculations of the correct therapeutic dose, which can result in avoidable adverse events. Participant-driven sporadic dosing patterns, such as taking medication holidays, for example, can also lead to problems such as unnecessary withdrawal symptoms or side effects.
Poor medication adherence gives an inaccurate picture of how a drug works in each patient population. It has a direct effect on the cost and duration of clinical trials. Crucially, it can delay the approval of investigational products – at a cost of between $600,000 and $8m [USD] a day in lost revenues.
OSP: What are some of the problems with medication adherence, and why is non-adherence a concern with clinical trials?
While medication nonadherence has been a concern for centuries, regulators have long accepted a degree of variation in medication-taking behaviors during clinical trials. This, they believe, is more reflective of the real-life situation and is part of the intention-to-treat (ITT) principle.
However, the combined advent of uniquely powerful medicines and reliable means to assess adherence has brought patient nonadherence into sharp focus.
Partial adherence or nonadherence is adversely impacting the interpretation of clinical trial results. It can result in underestimated efficacy of new drugs, sometimes to the point of trial failure, underestimated incidence of adverse effects, and/or overestimated dosing requirements for marketed pharmaceuticals.
Recent developments are only serving to compound the problem. Pharma is addressing increasingly serious diseases for which powerful medicine has a narrow therapeutic window, for example, and as trials become more inclusive and representative, less professional patients with poorer adherence habits are joining.
At the same time, COVID-19 has accelerated the adoption of decentralized trials, meaning there are fewer study visits that are known to reinforce adherence.
OSP: How have trials monitored medication adherence in the past, and what are some of the problems with traditional/bygone methods of recording and monitoring?
BV: Traditional approaches to adherence monitoring – such as pill counts, blood sampling, and HCP or self-reporting – are subjective and simply not sensitive enough to provide real value.
Counting returned tablets is the most commonly used adherence measure in clinical trials, but it is easily censored by participants. In addition, it only provides a summary of medication-taking behavior between visits, rather than an overall understanding of treatment initiation and dosing patterns.
Sponsors or CROs may also opt for the self-reporting approach, asking participants to record their doses in a patient diary or conducting study exit interviews, for example. This method is not only intrinsically open to inaccuracies and bias, but it places additional burdens on the study participant. The same is true of asking site staff or healthcare professionals to record adherence.
Monitoring drug or drug metabolites in blood, urine, or hair may seem a more evidence-based approach, but, again, it only provides a snapshot. Participants could engage, for example, in so-called “white coat adherence”, meaning they only take the investigational product the day before the visit. In addition, it is invasive, places an additional burden on participants and staff, and is largely restricted to use in the active arms of a trial.
OSP: Please tell us about your initiative around patient behavior—what will you be looking at, and what do you hope to determine?
BV: Existing models of behavior change, which could help sponsors and CROs to support participants to build healthy medicine-taking behavior, are not suited to clinical trials. They tend to be too complex and focus on the initiation, rather than the continuation, of behavior change.
That’s why AARDEX is working with psychologists to adapt the COM-B model, which focuses on capability, opportunity, and motivation, for use in clinical trial adherence. The aim is to support people to transition from a “reflective” state, at treatment initiation, to an “automatic” state, where taking their medication is an ingrained habit – and keeping them there.
At study onboarding, or the reflective stage, the investigator ensures the study participant has the capability (e.g. understanding of the protocol), opportunity (e.g. is trained on all drug delivery systems), and motivation (e.g. is invested in the objective of the study) to comply with the protocol.
The model then moves onto helping people build the medication into their day until it becomes a habit, or “automatic.” Teams can then use ongoing digital adherence monitoring to spot patterns that could be indicative of relapse to reflective mode, to then intervene with tailored approaches when necessary.
OSP: How might the collected data be used to track and possibly guide patient behavior?
BV: Electronic monitoring is the most objective and precise way to fully understand medication adherence during a clinical trial. It consists of smart drug packaging, such as connected inhalers, blister packs, and container caps, and powerful data analytics.
Microcircuitry in the packaging records dose administration and transmits that information to the study team’s software for analysis. Connected pre-filled syringes, for example, collect and send essential information such as whether the injection was completed, the time and date of administration, type of drug, batch number, and expiration date.
Once received, a cloud-based platform uses sophisticated algorithms to analyze medication-taking behaviors and flag any erratic dosing patterns in the form of data visualizations.
This allows site staff to identify those participants who may be at risk of poor adherence and take tailored action – whether that is more education on the protocol, offering tips on how remembering doses, or advice on managing side effects. In essence, it is a closed feedback loop in which the packaging monitors and the study team uses the resulting data to manage adherence.
OSP: Are there any technology solutions that can help encourage adherence? i.e. mobile apps, wearables, etc.
BV: Data from digital adherence monitoring can be integrated into third-party applications, such as patient-facing apps designed to build engagement and encourage adherence.
Step 0 of such a system is to provide onboarding screens to ensure participants have all the information they need to start and continue to follow the trial protocol. This might include dosing regimens, device use instructions, and information on the importance of adherence, as well as advice on developing strong medication intake behavior.
The journey does not stop there; it is key to support patients throughout the trial. People can use the app to view their scheduled appointments, reminders, and medication history, transfer their data to the central system, and access the site team.
This advanced approach is a feasible, reliable, and easily implemented method of quantifying medication adherence. It is continuous, so it provides an overall picture, and non-invasive, placing no additional burden on staff or participants.
OSP: Do you have anything to add?
BV: Patient adherence has been qualified as “Clinical Pharmacology’s Embarrassing Relative”. (Fossler 2014). There is strong evidence to suggest that poor adherence to protocol-specified dosing regimens is a long-neglected worldwide problem of striking magnitude. “Status Quo in drug development (i.e. ignoring medication adherence)” is no longer sustainable.
“Regulatory agencies should strongly encourage companies to not only quantify adherence in all clinical trials but should encourage the use of this important covariate in the analysis of those trials. It is long past time to bring patient adherence back into the clinical pharmacology family” (Fossler 2014).
