Remarque Systems

People, Processes, and Technology: The 3 Pillars of RBM

Risk-based monitoring. Everyone’s talking about it. Few actually know what it is, why they should care, and how to make it work for them. And many are laboring under misconceptions. Our goal is to set the story straight.

Risk-based monitoring (RBM) is not:

  • A mandate by the International Council for Harmonization (ICH) guidelines for Good Clinical Practice (GCP)
  • A streamlined version of Source Document Verification (SDV)
  • A complicated, expensive new technology

Risk-based monitoring is:

  • A modified version of the traditional clinical monitoring schema, characterized by promoting a risk mitigation strategy

Such strategies have been used for decades by a wide range of industries. The basic principle is to manage for quality by proactively managing risk: assessing it, monitoring it, and mitigating it as issues arise, so risks are detected and handled early, before they become problems.

How does RBM apply in the clinical setting? Traditional clinical monitoring oversees clinical efficacy and patient health during a clinical trial, typically through an in-person visit to an investigator site at a given frequency, such as every six weeks. Conversely, RBM combines on-site visits with remote monitoring (also known as centralized monitoring). It’s a dynamic strategy, whereby activities are modified based on pre-agreed parameters. The effectiveness of remote monitoring rests heavily on the quality of the data being monitored — and for that, technology becomes vital.

The operational components of risk management

Overall, managing risk is a responsibility of operations. Some risks are not unexpected; within the overarching trial design they are seen as strong possibilities, but worth the chance. Other risks are unknown, things that materialize in the course of a study. Both must be addressed when creating a risk-based monitoring plan. A plan that operationalizes risk management has three key stages:

  1. Identify risks and potential risks. Examine every aspect of the trial to pinpoint relevant risks that might affect patient safety or data quality. That includes looking at protocols, processes, and programs. It is also wise to consider regulatory considerations at this point.
  2. Monitor those risks. Technology can be tremendously helpful at this stage, providing dynamic real-time insight into data at the patient level, the site level, and the study level.
  3. Mitigate risks. Based on the risks identified in step 1, pre-plan a risk mitigation strategy that can be implemented as needed. Technology can also be helpful here, since regulatory authorities will want an auditable trail of actions that were taken, and reasons why: Was there an issue or was the action pre-emptive? When was the action taken? What was the result? A clear record of these answers can be extremely helpful.

The role of technology in RBM

Though technology supplies a powerful foundation for RBM, it is not the only essential factor. True RBM requires people who are well trained and have a deep understanding of and appreciation for quality management. It requires a clearly delineated, robust process for those people to follow. And then, finally, it requires technology to both underpin and advance those people and processes.

Such technology starts by collecting data from all functional areas across the study: clinical results; safety-related statistics; and study-, site-, and patient-specific data. Once aggregated, the system should visualize the data, so it is not only instantly accessible, it is instantly assessible. It must have strong remote monitoring capabilities — and it must allow that monitoring to be customized and focused at the site, adjusting for changes as needed during the course of the trial.

Of course, much of the value of such systems lies in machine learning and artificial intelligence. For instance, a simple user interface can create distance measurements, based on which algorithms cluster similar patients and sites. With that insight, investigators can not only relate a given patient to the average or median in a study, but, more specifically, to a similar cluster.

Machine learning can also dynamically identify outliers and pinpoint missing data with as few as three patients. Through increasingly robust knowledge libraries, investigators can begin to train machines to understand the nuances of therapeutic areas, disease states, and drug targets, enabling the machine to better recommend actions as issues are presented.

The continuous monitoring of data will cause the quality of data to improve — all of which will drive down study costs and improve patient safety. Yet none of this happens without human interaction — and human decision-making.

The role of people in RBM

Properly deployed, technology is tremendously useful in helping people swiftly identify anomalies, including risks and threats as they arise. Yet technology itself cannot even truly identify an issue — much less address it. Instead, it can flag issues previously identified by sponsors and CROs. This can help sponsors and CROs deploy mitigating tactics, often before the danger comes to fruition. Still, someone needs to identify those potential issues, program the system to recognize them, and then monitor and react to the system’s outputs.

The central monitor — the person who manages trial-wide data from a central location — is the keystone of risk-based monitoring, the air traffic controller of a clinical trial. First, they must help determine the algorithms and triggers that are appropriate to their particular trial. Then, they must evaluate how well each site is performing, triage tasks based on the review of patient-level data (by themselves or others), and trigger on-site monitoring visits.

At the other end, by properly utilizing the technology, site staff are freed from rote regulatory data management and can spend more time focusing on other critical factors of the trial, such as patient enrollment and compliance. Regular communication keeps these investigators in the loop, ensuring they are also involved in the quality management process.

The value of mitigating risk

As the scale, complexity, and cost of clinical trials have increased, the parallel evolution in technology and risk management processes offer new opportunities to manage quality through a strategy of active risk mitigation targeted to specific relevant activities. Leveraging people, process, and risk-based monitoring technology, such strategies increase patient safety and decrease costs, two goals that are the aim of every sponsor.

For more information, download our white paper Debunking the Myths of Risk-Based Monitoring for a New Approach to Quality Management.