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The Role of Source Data Verification (SDV) and Source Data Review (SDR) in Driving Clinical Trial Data Quality

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Like many business processes, clinical trial operations require planning, compliance with regulations, and coordination between multiple stakeholders.  Risk-based Quality Management (RBQM) of clinical trials is a targeted, strategic approach that supports project teams to focus on what matters most and thus place resources in the areas which bring the most significant value.  The aim of RBQM is to focus monitoring and oversight activities on those trial processes most likely to affect participant safety and data quality, to enable clinical operations teams to mitigate risks or address errors quickly and effectively before they compromise trial outcomes.  A significant component of RBQM is reduced source data review (SDR) and source data verification (SDV).  

By definition, source data verification is the process of ensuring that the data reported for analyses accurately reflect the source data at the clinical trial site, a comparison of source data against the CRF data (transcription errors).  Source data verification predominantly detects random errors that likely have little impact on the results of clinical trials. Source data review is the review of source documents in relation to the clinical conduct of the protocol.  Source data review focuses on areas that may not have an associated data field in the CRF or a system.  Historically, source data verification has been conducted for most of the CRF data; however, source data verification  of 100% of the data does not guarantee error-free results, and concentration on transcription accuracy does not guarantee data quality. Source data review instead focuses on the quality of data collection and compliance against the protocol and standard of care.  As a result, source data review tends to be more strategic, resulting in a heavier focus on the present and future proactive activities to maintain data quality.  

The landmark TransCelerate BioPharma’s position paper on risk-based monitoring (RBM) supports a shift from traditional 100% on-site monitoring source data verification.  The paper determined that only 2.4% of the queries in critical data were driven by source data verification, thus suggesting that source data verification has a negligible effect on overall data quality. 

On-site monitoring with the primary purpose of source data verification is resource-intensive, accounting for up to 25% of the total clinical trial cost. Despite evidence-based analysis demonstrating its infectiveness, and encouragement from regulators to develop strategic monitoring processes, source data verification remains ingrained in the clinical trial industry as the primary activity during on-site monitoring visits. However, recent analysis from organizations such as the Association of Clinical Research Organizations (ACRO) suggests a shift may be occuring (results in press).  

With the emerging RBQM methodology and evolving technology shift, clinical trial organizations are shifting from remote source data verification activities to more strategic quality management methods, such as remote source data review.  Source data verification should be considered one of many potential quality control mechanisms used to determine whether an acceptable level of accuracy has been achieved in the transcription of critical data. However, a heavy reliance on source data verification should not be taken as a mechanism to ensure study quality oversight. To determine the proper volume and targets for reduced source data verification & source data review, a critical first step is a protocol-based risk assessment to inform an intelligent monitoring strategy.

In ICH Guideline for Good Clinical Practice, one of the key themes is alignment with quality-by-design (QbD) principles in clinical trial planning.  The guidelines make it clear that the overall quality of a trial is driven proactively by designing quality into the study protocol and processes, with appropriate and fit-for-purpose use of technology. Therefore, the most accessible and most significant value gain is from a targeted and focused approach to reduced source data verification and source data review.  

Targeted Source Data Verification (TSDV) activities can be easily established using critical-to-quality factors to identify data and processes most likely to impact trial results.  These activities are best conducted within a unified platform to ensure sound audit readiness and efficacy.

In conclusion, as clinical trial operations continue to evolve, monitoring and oversight activities should focus on trial processes most likely to affect participant safety and data quality to address errors quickly and effectively, before they compromise trial outcomes.

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