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FDA, EMA Advise on Risk-Based Monitoring in Clinical Trials

Posted 17 July 2019 | By Ana Mulero 

FDA, EMA Advise on Risk-Based Monitoring in Clinical Trials

US and EU officials explained on Wednesday what their respective regulatory agencies look for in clinical trial risk-based monitoring (RBM) and how RBM can impact review times.
Under a cooperative agreement with the US Food and Drug Administration (FDA), the Duke-Margolis Health Policy Center convened the public workshop in Washington, DC for a debate on improving the implementation of RBM in clinical trials by identifying how regulators can help with some of the current barriers to widespread adoption of RBM. Participants looked for clarification around how regulators’ approaches to RBM differ.
FDA Office of Scientific Investigations (OSI) Director David Burrow stressed that “terminology is critical.” Having recognized that FDA and the European Medicines Agency (EMA) “may slightly differ in the terminology that we use in the risk-based quality management (RBQM) conversation,” Burrow identified common elements in RBM.
The elements comprise a three-part process to plan and develop RBM systems such that the end results align with the expectations of agency review teams, per Burrow. It begins with what Burrow refers to as “a necessary component for an effective RBM”—a risk assessment, followed by a “well-articulated, clean, crisp clear, appropriate protocol based on that risk assessment.” The risk-based monitoring plan can then be built on an appropriate risk assessment to be effective.
Burrow placed emphasis on including a plan that specifies the intent of an RBM system as FDA would not otherwise consider it to be “true RBM.” No plan could result in application delays following complete response letters or requests for additional information, among other regulatory actions at the agency’s disposal. Delays cost time and time is money, Burrow noted, highlighting an analysis OSI conducted of 334 clinical investigation summaries (CISs) over a three-year period. A CIS provides recommendations to FDA's Office of New Drugs. 
The analysis underscored the impact on review times by separating OSI recommendations into two buckets, with passive recommendations being those that conclude the data are reliable in support of the submitted application and active recommendations being those that prolong reviews. OSI found that 62 out of 334 CISs (19%) had at least one active recommendation, most of which were driven by no action indicated inspections and voluntary action indicated inspections. Data were reliable in support of the application in 81% of the cases.

Burrow explained that a sponsor who claims to have used RBM may be at adds with what FDA believes to be RBM, which is a challenge for the agency to assess and track RBM outcomes. But in "some instances where we have seen true RBM be implemented, we have seen a great correlation between the issues that were identified in the risk-based monitoring system and the issues we see in the application review on the back end."
EMA Scientific Administrator Camelia Mihaescu also stressed that a RBM plan should be based on the data of the risk assessment as well as be trial-specific. Mihaescu focused more heavily on the pairing of a risk assessment with a mitigation plan. “There should always be a connection between a monitoring plan and a risk assessment and mitigation plan,” Mihaescu said. 
Mihaescu further explained that EMA considers RBM in clinical trials to be an effective tool for addressing areas of risk, whether high or low, early in and throughout the drug development process and thus allow the sponsor to be better positioned when seeking to submit an application and bring a new product to the market. 

The slight deviations in how FDA versus EMA approach RBM should not be a deterrent to RBM adoption because regulators share the same interest as industry to have an absence of errors that matter, according to Burrow. Both FDA and EMA view RBM, if used correctly, and quality as two sides of the same coin.
Improving the Implementation of RBM Approaches

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