Bernard Vrijens, CEO & Scientific Lead, AARDEX Group08.05.21
Sponsors and regulators have long known that poor adherence to medication is a threat to clinical trial success. How to solve the problem, however, has not been so clear cut. Until now.
In recent years, digital adherence monitoring, with its ability to track doses, trace drug taking behavior, and inform individualized interventions, has emerged as an evidence-based way to leverage clinical trial outcomes.
In this article, we will set out the adherence problem, and how it can adversely affect research, before demonstrating how modern monitoring systems have the edge over traditional methods.
Adherence and trial failure
The reasons for study failure are as varied and complex as the trials themselves, but one common thread runs through many of them – poor medication adherence, which affects around 50% of all clinical trial participants.1
According to a 2018 review of data from the previous 30 years, the primary source of trial failure is an inability to demonstrate efficacy .2 One study, by Hwang et al, of 640 Phase III trials of novel therapeutics, found that 54% had failed in clinical development. Of these, 57% were attributed to inadequate efficacy.3
But this does not necessarily mean the drug did not work. The finding could, for example, be the result of incorrect dosing or an underpowered study,2 both of which are common consequences of poor medication adherence.
Safety is another common cause of study collapse, with Hwang et al finding it to be the root cause of failure in 17% of the Phase III trials analysed.3
However, unmanaged medication adherence often leads to distorted risks/benefits and safety concerns may be the result of the selection of an ill-fated dosing regimen or a total dose higher than needed for adherent patients.4
With it taking between 10 and 12 years and more than £550million4 to develop a new drug, poor adherence to the trial protocol , then, is a costly problem.
The problem with traditional methods
Sponsors and CROs have grappled with the financial and logistical problems of poor medication adherence for decades.
To date, they have been forced to rely on the only methods available – pill counts, blood sampling, and HCP or self-reporting. Yet these traditional approaches are not sensitive enough to provide real value.
Counting returned tablets is easily censored by participants. Moreover, it only provides a summary of adherence between site visits, rather than an overall understanding of treatment initiation and dosing patterns.
Self-reporting, in which participants record their doses in a diary, for example, is vulnerable to inaccuracies, bias and places additional burden on the study participant. The same is true with different methods of diaries including paper and digital apps, even if they have reminders and other advanced technology that record proof of ingestion. Resulting in poor data quality and an increase in fraud due to patient inconvenience.5
Similarly, monitoring drug or drug metabolites in blood, urine, or hair only provides a snapshot of adherence. So-called “white coat adherence”, meaning people only take the investigational product the day before their site visit, is a concern. It is invasive, burdensome, and its use is largely restricted to active arms of a trial.
The smart way to monitor adherence
Digital monitoring using smart packages is frictionless for patients, thus objective & precise and provides a holistic view of medication taking behavior.
The solution combines smart drug packaging, such as connected inhalers, blister packs, and container caps, with powerful data analytics.
Microcircuitry in the packaging records automatically dose administration and transmits the information to the study team’s software. For example, connected pre-filled syringes collect and send essential information, including whether the injection was completed, and the time and date of administration.
A cloud-based platform then uses sophisticated algorithms to analyze medication-taking behavior and uses data visualizations to flag any erratic dosing patterns.
By identifying participants who may be at risk of poor-adherence, study teams can tailor to that individual’s personal non-adherence drivers.
This advanced approach is feasible, reliable, and easily implemented. It is continuous, meaning it provides an overall picture, and non-invasive, placing no additional burden on staff or participants.
Crucially, it is evidence based. Studies have shown that smart package monitoring is 97% accurate, compared to 60% for pill counting, 50% for healthcare professional rating, and just 27% for self-reporting.6
Digital adherence smart packaging solutions, then, provide sponsors and CROs with the tools they need to improve medication taking behaviors, mitigating the risk of study failure and increasing their return on investment.
1. 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
2. Fogel, D. Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review. (2018). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092479/
3. Hwang, T., Carpenter., D. et al. Failure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results. (2016)https://pubmed.ncbi.nlm.nih.gov/27723879/
4. Breckenridge, A., Aronson, J., et al. Poor medication adherence in clinical trials: consequences and solutions. (2017). https://www.nature.com/articles/nrd.2017.1?WT.ec_id=NRD-201703&spMailingID=53536275&spUserID=ODkwMTM2NjI2OQS2&spJobID=1120295377&spReportId=MTEyMDI5NTM3NwS2
5. Larson., K, Areberg J., et al. Clinical Trials1–6. DOI: 10.1177/17407745211012683 journals.sagepub.com/home/ctj
6. Greener, M. Drug development: bench to bedside. (2013) https://www.magonlinelibrary.com/doi/abs/10.12968/npre.2010.8.2.46589 visited on 19 May 2021.
Dr. Vrijens 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.
In recent years, digital adherence monitoring, with its ability to track doses, trace drug taking behavior, and inform individualized interventions, has emerged as an evidence-based way to leverage clinical trial outcomes.
In this article, we will set out the adherence problem, and how it can adversely affect research, before demonstrating how modern monitoring systems have the edge over traditional methods.
Adherence and trial failure
The reasons for study failure are as varied and complex as the trials themselves, but one common thread runs through many of them – poor medication adherence, which affects around 50% of all clinical trial participants.1
According to a 2018 review of data from the previous 30 years, the primary source of trial failure is an inability to demonstrate efficacy .2 One study, by Hwang et al, of 640 Phase III trials of novel therapeutics, found that 54% had failed in clinical development. Of these, 57% were attributed to inadequate efficacy.3
But this does not necessarily mean the drug did not work. The finding could, for example, be the result of incorrect dosing or an underpowered study,2 both of which are common consequences of poor medication adherence.
Safety is another common cause of study collapse, with Hwang et al finding it to be the root cause of failure in 17% of the Phase III trials analysed.3
However, unmanaged medication adherence often leads to distorted risks/benefits and safety concerns may be the result of the selection of an ill-fated dosing regimen or a total dose higher than needed for adherent patients.4
With it taking between 10 and 12 years and more than £550million4 to develop a new drug, poor adherence to the trial protocol , then, is a costly problem.
The problem with traditional methods
Sponsors and CROs have grappled with the financial and logistical problems of poor medication adherence for decades.
To date, they have been forced to rely on the only methods available – pill counts, blood sampling, and HCP or self-reporting. Yet these traditional approaches are not sensitive enough to provide real value.
Counting returned tablets is easily censored by participants. Moreover, it only provides a summary of adherence between site visits, rather than an overall understanding of treatment initiation and dosing patterns.
Self-reporting, in which participants record their doses in a diary, for example, is vulnerable to inaccuracies, bias and places additional burden on the study participant. The same is true with different methods of diaries including paper and digital apps, even if they have reminders and other advanced technology that record proof of ingestion. Resulting in poor data quality and an increase in fraud due to patient inconvenience.5
Similarly, monitoring drug or drug metabolites in blood, urine, or hair only provides a snapshot of adherence. So-called “white coat adherence”, meaning people only take the investigational product the day before their site visit, is a concern. It is invasive, burdensome, and its use is largely restricted to active arms of a trial.
The smart way to monitor adherence
Digital monitoring using smart packages is frictionless for patients, thus objective & precise and provides a holistic view of medication taking behavior.
The solution combines smart drug packaging, such as connected inhalers, blister packs, and container caps, with powerful data analytics.
Microcircuitry in the packaging records automatically dose administration and transmits the information to the study team’s software. For example, connected pre-filled syringes collect and send essential information, including whether the injection was completed, and the time and date of administration.
A cloud-based platform then uses sophisticated algorithms to analyze medication-taking behavior and uses data visualizations to flag any erratic dosing patterns.
By identifying participants who may be at risk of poor-adherence, study teams can tailor to that individual’s personal non-adherence drivers.
This advanced approach is feasible, reliable, and easily implemented. It is continuous, meaning it provides an overall picture, and non-invasive, placing no additional burden on staff or participants.
Crucially, it is evidence based. Studies have shown that smart package monitoring is 97% accurate, compared to 60% for pill counting, 50% for healthcare professional rating, and just 27% for self-reporting.6
Digital adherence smart packaging solutions, then, provide sponsors and CROs with the tools they need to improve medication taking behaviors, mitigating the risk of study failure and increasing their return on investment.
1. 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
2. Fogel, D. Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review. (2018). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092479/
3. Hwang, T., Carpenter., D. et al. Failure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results. (2016)https://pubmed.ncbi.nlm.nih.gov/27723879/
4. Breckenridge, A., Aronson, J., et al. Poor medication adherence in clinical trials: consequences and solutions. (2017). https://www.nature.com/articles/nrd.2017.1?WT.ec_id=NRD-201703&spMailingID=53536275&spUserID=ODkwMTM2NjI2OQS2&spJobID=1120295377&spReportId=MTEyMDI5NTM3NwS2
5. Larson., K, Areberg J., et al. Clinical Trials1–6. DOI: 10.1177/17407745211012683 journals.sagepub.com/home/ctj
6. Greener, M. Drug development: bench to bedside. (2013) https://www.magonlinelibrary.com/doi/abs/10.12968/npre.2010.8.2.46589 visited on 19 May 2021.
