As a Data Focused CRO, Quanticate offers Risk-Based Monitoring (RBM) technology combined with Statistical Consultancy in order to incorporate risk analysis in your trial as early as the development of your Statistical Analysis Plan (SAP) and Trial Master Plan (TMP). To achieve a risk-based approach, centralized statistical monitoring techniques are used so that sponsors can visualise signals, which can be actioned, escalated and resolved.
RBM is a clinical trial-monitoring technique that fulfils regulatory requirements but moves away from 100% source data verification (SDV) of patient data. It employs various tools, platforms and dashboards to identify signals, which indicate potential issues with (for example) trial conduct, safety, data integrity, compliance and enrolment. This allows the study team to concentrate on high value tasks and focuses resources on specific trial-related matters.
RBM means that the volume and frequency of monitoring is reduced, as data are only verified at high risk sites based on triggered events or certain pre-defined critical events in the study. The quality of the trial data can be improved by identifying, assessing, monitoring and mitigating risks.
Regulatory authorities recognize the potential of RBM to improve the conduct of clinical trials of all phases and have published guidance documents on RBM, encouraging sponsors to apply risk-based approaches to study management. RBM is not yet absolutely mandated by any regulator; however, both FDA and EMA accept that less data review is appropriate in lower risk studies and in lower risk periods of an initially higher risk study.
The monitoring can be performed centrally and is targeted to patients or sites based on outlying, inlying, erroneous, operationally deficient or potentially fraudulent data.
FDA guidance outlines three steps in an RBM approach:
For critical data to be flagged as causing a potential risk, a sponsor must firstly identify the expected/acceptable values and parameters. Intelligence from previous studies can be drawn upon to help identify and quantify these metrics as high, medium or low risk.
The mitigation for a given identified risk can change throughout the trial and the categorization of the risk does not need to be entered when initially working with the RACT (Risk assessment categorization tool). Examples of high risk data points include any of those which impact patient safety, the use of trial sites with little or naive experience of clinical trials or endpoint data categories.
When risks have been identified they can be visualized using a 'traffic light system' for clinical operations to assist in conveying these findings to site, a risk assessment must be conducted which involves investigation of the risk and its origin (source data review), and the implementation of risk mitigation methodologies, enacting corrective action to prevent further risks and resolve current risks. These may include re-education of the site, motivational visits, amending a recruitment plan, escalation to a global level or in extreme cases the issuing of warning letters.
At Quanticate we can provide the consultancy required for the change management aspect of RBM. We recommended consideration of RBM strategies for your trial and development of the required monitoring plan early in the development process.
FDA guidance states that a clinical/trial monitoring plan (CMP/TMP) must ‘’describe the monitoring methods, responsibilities and requirements of the trial”. This critical document will stipulate which data points need to be monitored, the frequency of monitoring coupled with communication and escalation plans for all stakeholders involved in the trial.
The RBM strategy above is becoming an integral concept in pharmaceutical clinical research, which has the potential to reduce clinical costs and improve data quality, while simultaneously reducing time to approval of an Investigational Medicinal Product (IMP). The FDA are now, as an integral part of their approval process performing statistical analyses on all data sets submitted for approval, hence, it is strongly advised that all studies both ongoing and about to commence, integrate some degree of RBM and statistical monitoring to meet these recently implemented standards.
At Quanticate we can offer RBM via our portal and our custom built, in-house, centralized monitoring platform and risk dashboard. All selected clinical trial data will flow within the customized dashboard. Based on the pre-set parameters and agreed risk factor parameters, the dashboard displays data within a heat map that enables the identification of outliers and risks. Potential erroneous data are identified earlier, hence improving the quality of the trial data and enhancing patient safety. SDV can be reduced and sites that are performing well will not require such rigorous monitoring, resulting in lower costs, for example CRA travel time.
In summary, the RBM Strategies are:
In this webinar, you will learn how implementation, evolution and change management are critical for a successful remote monitoring program. But how does a remote monitoring program harmonize with current Source Data Verification practices?
This ebook will explain rSDV's definition, present explored and piloted practices of conducting rSDV, the shortcomings of traditional monitoring and 100% SDV, and showcase the cost savings that can be incurred, as well as process efficiencies compared to traditional trial monitoring when using an rSDV approach.