The International Council for Harmonization’s addendum to the ICH E6 Guideline for Good Clinical Practice (ICH E6 R2) and EU regulation 536/2014 strongly advocates the adoption of risk-based monitoring (RBM) of clinical trials. Despite the regulator’s advocacy and the perceived benefits of RBM, industry adoption has been quite slow due to misconceptions about what type and level of compliance are acceptable in the eyes of the FDA and EMA.
In this article, we attempt to debunk 3 important myths that surround the implementation of RBM and hope that moving forward both sponsors and CROs will more aggressively adopt and implement RBM strategy in the true sense.
MYTH 1
A risk-based monitoring plan to be effective should amount to 100% centralized monitoring.
Just migrating to 100% centralized monitoring without having a strategy for what to look for, when, or why is not risk-based monitoring!
FDA guidance encourages greater use of centralized monitoring methods where appropriate and also anticipates that pharma sponsors would continue to use some on-site monitoring for the foreseeable future. The clinical research industry, however, is still ignorant about how to achieve the balance between the triage of centralized, remote and on-site monitoring.
A true RBM strategy starts with a risk assessment, which is used to develop a well-articulated clinical trial protocol. The assessed risk and protocol are then used in combination to create a fit-for-purpose monitoring plan that is tailored to the critical risks of the trial. A risk-based monitoring plan could have all three monitoring types – on-site, remote and centralized – that are risk-based, OR you could have all three monitoring types that are not risk-based and futile.
So, the take-home message is that RBM strategies should involve greater use of centralized and remote tools, as well as various analytical tools to identify trends, outliers, and systemic errors in a risk-based approach. Regulations do advise to move away from 100% source data verification, but that does not equate to 100% centralized monitoring. As per FDA’s industry guidance on risk based monitoring approach, one should focus on critical study parameters and utilize a combination of monitoring activities to oversee a study effectively.
MYTH 2
RBM should be added on top of the traditional monitoring plan to drive better compliance.
Risk-based monitoring plans, to be effective, must be built on appropriate risk assessment, identification, and mitigation. This is essential, but it is a common misconception across the spectrum that you could take a risk-based monitoring strategy and put it on top of an already executed protocol. For an industry as heavily regulated as clinical research, everybody is amenable to add an extra layer of quality/safety oversight.
The industry though willing to incorporate components of risk-based monitoring over and above the traditional form of on-site monitoring which is still considered the gold standard for data accuracy and integrity; is not ready to let go of the redundant 100% SDV, be it as laborious or as costly as it can be. Sponsors are anxious and worry that if we do less monitoring of the data, we may miss out on something, and we get less quality. The matter of fact is that there will be errors in the data despite the most stringent monitoring and it is fine as long as these errors are not critical or systemic.
Sponsors need to change this approach and understand that RBM should be considered as a part of an overall quality-by-design approach to clinical trial protocol development and conduct – tailored to match the specific risks of each study. With the right RBM in place which picks up systemic errors that matter, they should not be worried about missing something that is random.
MYTH 3
The main function of RBM is to reduce the SDV burden. Period.
We all unanimously agree that there is lots of source data review and verification of clinical data, that goes on during clinical trial conduct. Ironically, the modern EDC systems which put more emphasis on SDV have made the process counterproductive rather than increasing efficiency. RBM along with sampling of data that should be SDV’ed has been touted as a methodology to decrease the percentage of data that gets verified and thus reduce the rising cost of clinical development. However, sampling alone without a risk mitigation system does not qualify as an RBM plan to reduce SDV.
RBM asserts that all data entered in eCRF is not identical in terms of risk.
It analyses which data is important and thus allows us to identify high-risk data points that should undergo source data verification. With RBM, 100% SDV is performed, but only on sample data points that are prone to errors in interpretation or transcription and hence could highly impact the data quality and the clinical trial outcome. Less time is focused on data deemed less important, allowing monitors to focus their time on managing identified risks and other issues.
Another RBM method to reduce SDV is to utilize automation in collecting as much source data as possible using direct data transfers from an automatically generated source. Since there is no manual data entry, the need for SDV is eliminated using a validated transfer. Central laboratory report values, e-source such as electronic medical records, electronic patient-reported outcomes (ePRO) are all examples of direct capture technologies that are utilized under the realm of RBM to reduce the burden of SDV.
Hence it would be right to say that the goal of RBM is to optimize the efficiency of SDV rather than reducing SDV percentage per se.
“Quality is independent of Regulatory Compliance”.
