As experts in biostatistics, Quanticate have been actively involved in advising and implementing Risk‑Based Monitoring solutions utilizing centralized statistical monitoring technologies developed by our in-house team of expert statisticians.
Whilst there has been a lot of interest in recent years around risk‑based monitoring and adaptive methodologies to optimize clinical development, the recent addendum to the ICH E6 (R2) has now moved the use of risk‑based approaches from something that innovators were using, to an essential requirement of all clinical trials.
As explained in the new ICH guidelines; “The sponsor should develop a systematic, prioritized, risk‑based approach to monitoring clinical trials..… The sponsor may choose on-site monitoring, a combination of on-site and centralized monitoring, or, where justified, centralized monitoring. The sponsor should document the rationale for the chosen monitoring strategy (e.g., in the monitoring plan).”
A risk‑based approach therefore requires consideration at an early stage and details may need to be provided in the study protocol and Statistical Analysis Plan (SAP), as well as the monitoring plan. Utilizing the skills of an experienced statistician will help to optimize the study, incorporate a risk-based targeted approach and ensure approval. In order to determine the degree on centralization, statistical methodologies are needed. The guidelines recognize this by stating, “Centralized monitoring is a remote evaluation of accumulating data, performed in a timely manner, supported by appropriately qualified and trained persons (e.g., data managers, biostatisticians).”
One of the keys to successfully implementing a centralized monitoring solution is ensuring that an appropriate method of data review is included in the study design. As such, it is important to work with clinical data management to collect data, use a tool to visualize the data and involve statisticians in the review of the data to direct the Clinical Research Associate (CRA) to target specific sites for additional Source Data Verification (SDV).
Having expert input into the protocol and SAP to help reduce on-site SDV and allow centralized review will reduce study monitoring costs, whilst assuring data quality and patient safety.
ICH E6 (r2) provides insight into the expectations by stating:
Review, that may include statistical analyses, of accumulating data from centralized monitoring can be used to:
(a) identify missing data, inconsistent data, data outliers, unexpected lack of variability and protocol deviations.
(b) examine data trends such as the range, consistency, and variability of data within and across sites.
(c) evaluate for systematic or significant errors in data collection and reporting at a site or across sites; or potential data manipulation or data integrity problems.
(d) analyze site characteristics and performance metrics.
(e) select sites and/or processes for targeted on-site monitoring.
In practice, monitoring can be performed centrally and is accomplished by targeting patients or sites based on outlying, inlying, erroneous, operationally deficient or potentially fraudulent data. Use of a tool that incorporates statistical algorithms to identify risk factors is required and access to skilled statisticians can be beneficial in accurately interpreting results.