The International Council for Harmonization addendum to the ICH E6 Guideline for Good Clinical Practice (ICH E6 R2) and EU regulation 536/2014 strongly backs the adoption of risk-based monitoring (RBM) of clinical trials.
Despite the regulatory advocacy and the perceived benefits of RBM, industry adoption is still slow due to misconceptions about what type and level of compliance are acceptable in the eyes of the FDA and EMA.
So, in this article, we attempt to debunk three important myths about RBM so that the clinical trial industry effortlessly adopts and implements the RBM strategy in its practices.
Myth 1: To Generate A Highly Effective Risk-based Monitoring Plan, It Is Essential To Achieve 100% Centralized Monitoring
Just migrating to 100% centralized monitoring without having an effective strategy for what to monitor, when to monitor, and why to monitor is not risk-based monitoring!
FDA guidance encourages greater use of centralized monitoring methods where appropriate. FDA guidance also anticipates that pharma sponsors should continue to use some on-site monitoring for the foreseeable future. However, the clinical research industry is still ignorant about balancing the triage of centralized, remote, and on-site monitoring.
A right RBM strategy starts with a risk assessment, which is then used to develop a well-articulated clinical trial protocol. The assessed risk parameters and protocol are then used in combination to create a fit-for-purpose monitoring plan tailored for assessing critical risks of the trial.
A truly risk-based monitoring plan can incorporate all three types of monitoring, on-site, remote, and centralized - in a way that is effective and efficient in mitigating risks. However, a monitoring plan that does not consider risks potentially might render all three types of monitoring futile. It is critical to ensure that the chosen monitoring approach aligns with the identified risks, and is implemented strategically to effectively and efficiently manage the identified risks.
To achieve the above-stated goals, RBM strategies should involve increased use of centralized and remote tools, along with various analytical tools to identify trends, outliers, and systematic errors in a risk-based approach.
Regulations do advise moving away from 100% source data verification, but that does not correlate to 100% centralized monitoring. As per FDA’s 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 To The Conventional Monitoring Plan To Drive Better Compliance
For risk-based monitoring to be effective, it is crucial to establish a solid foundation through appropriate risk assessment, identification, and mitigation. However, it is a common misconception that risk-based monitoring can be implemented on top of an already existing protocol. For a heavily regulated industry such as clinical research, everybody is amenable to adding an extra layer of quality/safety oversight.
The clinical trial industry is willing to integrate risk-based monitoring with conventional on-site monitoring, which is considered the gold standard for data accuracy and integrity. However, the industry is still hesitant to eliminate the outdated practice of 100% SDV, even though it can be costly and labor-intensive. Sponsors are worried that reducing the amount of data monitoring might lead to lower data quality. But in reality, even with relentless monitoring, it’s inevitable to have some data errors. However, as long as these errors are not critical, the errors can be accepted.
Sponsors must shift their approach and recognize that risk-based monitoring should be integrated as part of an overall quality-by-design framework for developing and conducting clinical trial protocols. The approach can be customized to address the specific risks associated with each study. By implementing an effective RBM strategy that identifies and addresses systemic errors of significance, sponsors can alleviate concerns about overlooking random issues.
Myth 3: The Main Function Of RBM Is To Reduce The Burden Of The Source Data Verification (SDV)
It is acknowledged that a substantial amount of source data review and verification is involved in clinical trial conduct. Ironically, the advent of modern Electronic Data Capture (EDC) systems, which prioritizes source data verification, has often hindered efficiency rather than enhancing it. Risk-based monitoring is proposed as a methodology to address the above-stated issue by allowing for selective SDV, thereby reducing the ever-increasing costs of clinical development. However, it is critical to note that sampling alone, without a comprehensive risk mitigation system, does not qualify as an effective RBM plan for reducing SDV.
Risk-based monitoring recognizes that not all data entered in the electronic Case Report Form (eCRF) carries the same level of risk. It analyzes which data is critical and allows identifying high-risk data points that should undergo source data verification.
In risk-based monitoring, 100% source data verification is conducted but targeted toward sample data points that are more susceptible to errors in interpretation or transcription, which can significantly impact data quality and the outcome of the clinical trial. Less emphasis is given to verifying data that is less critical, allowing monitors to allocate their time and resources to managing identified risks and addressing other important issues.
Another approach within RBM to minimize the need for source data verification is automation for capturing a significant amount of source data. Automation is achieved through direct data transfers from sources that are generated automatically. By eliminating manual data entry and employing validated transfers, the necessity for SDV can be significantly reduced. Various technologies such as central laboratory report values, e-source systems like electronic medical records, electronic patient-reported outcomes (ePRO), and electronic clinical outcome assessments (eCOA) are all examples of direct capture methods that fall under the umbrella of RBM, effectively alleviating the burden of SDV.
Therefore, it is accurate to state that risk-based monitoring is used to enhance the efficiency of source data verification rather than solely reducing the percentage of SDV.
