Since the U.S. Food and Drug Administration (FDA) published its industry guidance "Oversight of Clinical Investigations − A Risk-Based Approach to Monitoring"1 in August 2013, the topic has taken the industry limelight, as companies strive to develop the best approaches and overcome challenges. The intent of risk-based monitoring (RBM), a paradigm shift in the way clinical trials are monitored, is to enhance patient safety, improve the quality of clinical data, and drive efficiencies.
For many years, the gold standard in clinical research to achieve these goals has been 100% source document verification (SDV), where clinical research associates (CRAs) check every data point on the information reported by investigators against source records to ensure the information is complete, accurate and valid. However, SDV has shown a negligible effect on data quality. In fact, Medidata found that after observing several thousand studies in its metrics warehouse, the median percentage of data corrected per trial was only 4.3%. After removing corrections made during the initial entry of each eCRF (electronic case report form), the resulting impact was a miniscule 2.7%.2
To improve sponsor oversight of clinical investigations, the Food and Drug Administration (FDA), European Medicines Association (EMA) and Pharmaceuticals and Medical Devices Agency (PMDA) recommend an RBM approach. RBM utilizes a combination of monitoring strategies, a greater reliance on centralized monitoring and statistical assessments to guide site monitoring visits, as well as a sharp focus on critical study parameters, and advanced technical capabilities. Clinical trial operations and technology are designed to bring together metrics and data to increase efficiencies, safety and quality and make data-driven decisions.
The FDA guidance highlights the importance of documenting the monitoring plan after assessing the project risks and needs. Sponsors are encouraged to take a flexible approach, analyzing ongoing data to continuously assess and adjust the monitoring strategy.
Utilizing RBM, targeted monitoring replaces calendar-based visit schedules with data-triggered visits, concentrating on sites with a higher workload and a greater need for support and monitoring. Centralized remote monitoring reduces costs and proactively addresses risks. Another benefit is that risk-based SDV, rather than 100% SDV, reduces the number of data points CRAs must source-data verify on site, reducing their workload and saving visit costs and time.
The traditional practice of 100% SDV led to a focus on the smallest detail at the expense of assessing overall performance and key data quality. As a result, important study aspects were likely overlooked.
Centralized monitoring proactively identifies and prevents inadequate site behaviors and processes early. Remote monitoring and data analysis are more efficient compared to solely focusing on reducing the amount of SDV required and reducing visits to sites where there may be a problem. The change in focus enables trial monitors to concentrate more on preventing quality issues from occurring than on only fixing problems.
RBM is a fundamental change in business and organizational processes, requiring senior management support for effective implementation. Managers must be committed to implementing this new initiative. To make the transition, effective process and change management practices, including staff retraining, are essential. Clinical CRAs and clinical project managers (CPMs) may find it difficult to change the way they have been working for many years, and some can be concerned about retaining their jobs.
At the beginning of a trial using RBM, study-specific key risk indicators (KRIs), which focus on critical known risks, are identified and defined as a function of set thresholds. KRIs are summary statistics that can reveal deviations in the study conduct or inadequate processes at certain centers. They are data and trial specific based on established parameters of risk, and change from study to study.
KRIs must be easy for study teams to understand and translate into action, and be linked to specific action and escalation paths. Advanced technology with a powerful visualization capability can enable study teams to efficiently incorporate KRIs into the study management process.
KRIs can be specified for:
The RBM system should also have an oversight risk score dashboard, and show weight controls for KRIs, historical risk score trends and the risk score compared to monitoring rates.
Visual Analytics Empower RBM
Efficiently gaining critical insights from the risk-based monitoring of clinical trials and quickly identifying issues is essential for clinical and operational effectiveness. An important tool for efficient centralized monitoring is a platform that can accelerate data collection and interpretation. The ideal platform should continuously and automatically consolidate data from the many disparate systems used to collect trial data, allowing trial oversight through real-time risk assessment.
Advanced technology for RBM should enable interactive, visualization-based data discovery for risk assessment, and make trial information from multiple sites easy to interpret and evaluate. Information on trial progression − such as enrollment, budget, and milestones − must be readily available to study teams along with data to assess protocol violations, site performance and dropouts.
The system should be flexible, with standard KRIs across protocols, but allowing KRI variability. Flexibility is also achieved when each KRI has an associated default RBM visualization, which can easily be modified or replaced. Users can freely explore data to any level of detail, significantly accelerating decision making. Repeatability is the key to leveraging knowledge derived from each RBM study.
Figure 1. Complete overview of the risk model and action status, with visibility into specific risk triggers for each site.
Simple, statistically driven visualizations with real-time calculations and interactive visual interpretation can be combined to detect risk, producing aggregate risk scores per site and contain a metrics overview dashboard. This would indicate sites with greater risk, which require more oversight.
Study managers can perform optimal study management utilizing visual analysis capabilities to identify trends and outliers, as well as analyze country and site performance. This data-driven monitoring enables CRAs to prioritize their work detecting issues and identifying protocol violations.
Traditional systems for managing clinical trials typically include a combination of software and paper-based processes. These systems collect tremendous amounts of data, but do not necessarily enable stakeholders to identify unfavorable trends and potential risks. Newer systems enable self-service discovery to drastically reduce reliance on IT and eliminate delay related to data preparation, report building and spread-sheet version control.
Figure 2. Recommended Actions
Risk-based monitoring utilizes objective data to proactively monitor trial behavior, detect the signal from the noise, and make data-driven decisions. The objectives are to reduce costs, time and risk in clinical trials and improve quality by design. RBM uses scientific methods to design monitoring strategies based on the risk factors associated with each clinical trial protocol. This holistic approach includes trial design, site monitoring, central monitoring, and meta-analysis across trials.
The adoption of RBM is increasing as companies provide greater management support, staff training and more sophisticated technology systems. Technology platforms that enable continuous monitoring with near real-time intuitive visualizations, analytic dashboards and applications will allow issues to be identified and addressed early, improving study safety and efficiency.