Medication Adherence Platforms: A New Way to Optimize Clinical Trial Outcomes
About half of new drug compounds fail to demonstrate efficacy in therapeutic trials. The root cause - low medication adherence.
Most clinical trial failures can be attributed to a lack of necessary efficacy data to support trial claims. But that’s often not the root cause – it’s a symptom brought on by low medication adherence to trial protocol.
With average trial adherence rates of only 43 to 78 percent, it’s no wonder that trials are failing to demonstrate efficacy. Data from noncompliant patients can affect trial results to such an extent that they can make or break a candidate drug.
Creating a strategy for better medication adherence should be on the priority list for all clinical trial teams. The following four approaches can help trial managers, investigators, researchers and even pharmaceutical sponsors take control of medication adherence and compliance, improve data analysis and reporting, and achieve higher quality clinical outcomes.
Tap into the latest tools to monitor, analyze and improve your data
Clinical researchers need strong, repeatable data for efficacy results to be justifiable. Medication adherence is a key determinant of the data quality. Research shows that medication adherence in clinical trials is both poor and highly variable among groups and individual patients, with only 34 percent of patients taking medications as prescribed. It is critical for clinical trials that professionals move toward better adherence strategies that support robust data collection and encourage better adherence.
The first step is determining which participants are adhering or are noncompliant, and for that, you need a tracking mechanism and adherence data. Real-time access to data confirms whether participants are taking the correct dose, on or off schedule, and helps researchers work with participants to stay on track or improve their behavior. It also can be used to remove them from a study. The ability to document behaviors, timelines and other data adds credibility to these decisions, which is not possible through self-reporting, pill counts or other traditional tools.
There are many new tools available that can help patients remember when to take their medications, but only a few that integrate smart devices with the management platform that provides the data and reporting. Smart device and software-based adherence platforms that offer the necessary tracking and reporting features don’t have to be complicated or expensive. They can also add enormous value to a trial without requiring participants to do anything differently. Because trials rely on data quality, look for a platform that offers a real-time monitoring solution. This allows trial managers to make adjustments to adherence activities in real time, rather than a platform that simply reports on the past.
Manage behaviors that impact power and sample size
Power and sample size are critical components of trial data and justification. But even the best-designed trials can be delayed or derailed because they no longer have the required power within their compliant sample size – the lower the adherence, the greater impact on power.
This is a huge issue because incomplete data means decisions around dosing efficacy and safety might be made from faulty information and may prevent or delay a trial from moving forward. We all know the basic rules for recruiting: avoid enrolling participants likely to have low adherence rates and focus on trial design and settings (location, etc.) that limit barriers to adherence.
What else can we do to manage adherence so we achieve the expected power and sample size?
Real-time information for time and dosage on a patient-by-patient basis offers critical visibility into the data required to support power. It also enables correction of nonadherence through counseling and/or removing “professional” or “trouble” patients. By monitoring activities in real time, trial managers can act immediately on power-reducing behaviors so you don’t waste time collecting poor data.
By improving adherence by 1,000 or even 5,000 basis points, it’s possible to reduce sample size and save costs (or keep costs from rising). This visibility can also help make dosing titration decisions faster or prove a link between adherence and efficacy/safety, allowing researchers to make a supportable decision to submit findings to regulators.
Improve on-schedule dosing for better results
When participants skip dosages, take medications off schedule, or don’t adhere to trial requirements, the efficacy data needed to move a trial from Phase 2 to Phase 3 can be highly compromised. In order for a trial to move forward, the correct dosing, drug-drug or drug-food interaction definitions and other data must be determined in Phase 2. Weak efficacy data is a key reason why less than 40 percent of trials move to Phase 3.
Until recently, clinical trial tools for collecting the necessary data have been limited and flawed. Data collected using participant feedback or basic monitoring can be inaccurate (knowingly or unknowingly) or simply not provided. With each uncertainty, data is questioned, power is reduced and trials fail.
The idea behind a successful clinical trial is to limit the flexibility around factors like dosing and intervals. Systems like the CleverCap™ adherence platform can accurately record the multiple data points required to identify strong or poor adherence, critical dosing and timing data needed to understand interactions. By having this data at your fingertips, trial teams can be confident that their data is accurate and take measure to limit inconsistent behaviors that might compromise efficacy.
Move toward data-driven adaptive trials
The problem that researchers are facing today is that they do not know if efficacy and/or safety issues are related to the drug or adherence. Currently, researchers have limited tools for making dosing decisions, which makes it difficult to hone in on specific positive efficacy results while reducing ineffective combinations.
Moving toward adaptive trials allows the trial to change course as it progresses, relying on data to make changes to protocol instead of waiting for the next trial. When components of this data are accessible in real time – such as whether participants are adherent to protocol – researchers can more easily eliminate uncertainties and focus on true indicators and results, adapting with more confidence. For example, if a particular medication combination or dosage appears to be more successful, researchers might increase the proportion of participants receiving the more successful dosage.
The problem that researchers are facing today is that they do not know if efficacy and/or safety issues are related to the drug or adherence. Currently, researchers have limited tools for making dosing decisions, which makes it difficult to hone in on specific positive efficacy results while reducing ineffective combinations. By having stronger (more powered) data collection on the more effective combinations, a trial can move into its next phase with a more targeted desired outcome and design.
By using adaptive techniques, researchers can reduce the time spent addressing outcome variations from inconsistent adherence after the trial has ended. With access to real adherence data, researchers know which participant data needs to be set aside for further review or segmentation.
About the author: Moses Zonana is CEO of CleverCap. CleverCap is a trademark of Compliance Meds Technologies, LLC.
Solving these key challenges will help clinical trial professionals get stronger data, forecast trial costs, improve statistical power and move forward faster. To learn more about optimizing clinical trial outcomes and medication adherence platforms – such as CleverCap, download the e-book: How poor medication adherence is damaging your clinical trial data and how to fix it, fast.
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