By Chip deVillafranca and Jonathan Andrus, BioClinica
When it comes to site monitoring, pharmaceutical companies have traditionally taken a conservative approach, performing frequent on-site monitoring and 100 percent verification of all data. This practice goes beyond what’s required, says the FDA in its Guidance for Industry: Oversight of Clinical Investigations — Risk-Based Approach to Monitoring, issued in August 2013. The agency asserts that sponsors adopted current practices based on a “perception” that 100 percent source data verification (SDV) was the FDA’s preferred way to meet monitoring obligations. Now it is trying to change that perception, citing academic- and government- sponsored research that has been successfully completed with less extensive on-site monitoring methods. The agency suggests monitoring strategies with a modern, risk-based approach and encourages greater use of off-site and central monitoring that employs technological advances in replacement of 100 percent SDV.
TransCelerate BioPharma, Inc. is helping to drive and speed adoption of this approach, making it the first of five key initiatives aimed at improving clinical trial efficiencies. Its Risk-Based Monitoring Methodology position paper issued in May states, “Current operational practices used in clinical trials are expensive and do not guarantee data quality.” The consortium points to modernization utilizing technology enablers that create efficiencies without impacting subject safety. Both the FDA and TransCelerate suggest making this change allows a shift in focus from manual aspects of data quality to what’s really important: patient safety, endpoints, informed consent, drug management, protocol training, and other study aspects.
In the current model, estimated costs for on-site monitoring with 100 percent SDV range between 20 and 30 percent of total study costs. A significant amount of the monitor’s time is spent checking for data entry errors, when in reality the FDA is looking at the overall data quality plan, not at every data element. Previous studies have shown that only 2.4 percent of data corrections occur as a result of SDV. With appropriate metrics and remote-review techniques, reduced verification can be employed with no loss of data quality.
Comprehensive risk-driven approaches rely on visibility into clinical data and operational key performance indicators to enable centralized review and monitoring. An electronic data capture (EDC) solution that captures site activity and clinical data in real time is essential, but this must be integrated with metrics from a clinical trial management system (CTMS). Achieving a holistic view of clinical sites, both past and present performance, through robust reporting and analytics tools is the cornerstone of any riskbased monitoring strategy.
As sponsors rarely work with a single vendor, multiple eClinical systems are typically already in place. Before a new monitoring approach can be implemented, an organization must ask: “Are we able to get the data out of where it is and into an analytics system to review and act on it?” Sponsors will need the ability to view data from across all systems, such as site initiation, document approvals, subject enrollment, data capture metrics, protocol deviations, adverse events, timeliness, and staff turnover — essentially all study activity.
A system’s location is immaterial as the Internet allows it to be located anywhere, whether cloud-based, on-site, or elsewhere. However, the APIs and interfaces are critical. Shifting to a strategic risk-based approach hinges on having immediate access to clinical and operational data, both current and historic. Continual assessment of data over the life of the study will indicate whether the site-monitoring plan needs adjustment.
What’s Your Data Telling You?
Centralized monitoring allows monitors to see patterns and detect problems early. It helps them to identify whether something is meaningful and requires action, such as when a protocol change is needed or a site needs extra support. Consider the example where a monitor is looking at 100 sites and sees that data entry took three weeks to do at all but one site, which finished in one week. An anomaly like this should prompt the monitor to check into whether there is a systemic problem, fraud, or something else. With the right analytic tools in place, potential issues can be seen and resolved before they escalate.
All of this data presents a challenge for executives and project leaders: With so many metrics across multiple domains, how do you boil them down into something useful? Each study sponsor must decide how to weigh certain metrics at the program and site level and even by study phase. Tools are available to execute the plan in the field and guide monitors at the site level. The EDC system guides them as to what data needs to be verified, and a robust CTMS collects operational data to drive the process. Reporting and analytical tools are available to aggregate data across multiple systems and even multiple studies. The aim is to get a 360-degree, high-level, real-time view across all of your clinical trials with the ability to drill into specific studies and sites to take action.
Reshaping the Monitor’s Role
Monitors have been conditioned to check every data element in the casebooks they review. This new risk-based approach transforms their role. Monitoring this new way requires a behavioral as well as cultural shift, one that takes some getting used to with new thinking on everyone’s part. Reduced SDV allows monitors to focus on more important site activities of higher value. With a solid plan and the right tools in place, monitors can be selective in what they review, based on a documented and objective monitoring plan.
Simply put, this is a better way of monitoring and a more effective use of resources. Efficiency, quality, and the ability to scale and run studies without unnecessarily overburdening personnel are just some of the advantages. As monitors visit sites less frequently, it will also lower costs. Finally, from a clinical operations perspective, leveraging technology makes better use of data, allowing an organization to detect problems earlier, make more informed decisions, and efficiently plan for future studies.