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With the emergence of new technologies for data collection, the continued impact of the COVID-19 pandemic, and the increasing number of partially or fully decentralized clinical trials (DCTs), the importance of risk-based monitoring (RBM) and the larger risk-based quality management (RBQM) framework in clinical trial management is increasing. RBM and RBQM focus on the detection of events or trends that impact trial quality in terms of participant safety and data integrity. In 2019, the Association of Clinical Research Organizations (ACRO) began a landscape survey of RBM/RBQM implementation in ongoing clinical trials. Initial results of this survey, representing full-year data for 2019, were reported previously. Here, we present full-year landscape data for 2020 drawn from 5,987 clinical trials ongoing at the end of 2020, including 908 new studies started that year. Of these trials, 77% implemented at least one RBM/RBQM component, an increase from 47% for studies ongoing at the end of 2019. We also observed increased implementation for three of the five RBM components included in the survey. Centralized monitoring decreased nominally in 2020 compared with 2019. Although the percentages of 2020 trials incorporating reduced source data verification (SDV) and reduced source data review (SDR) increased from 2019 to 2020, these numbers are still low considering the large percentage of trials implementing at least one RBQM component. In the current clinical trial landscape, as more DCTs are launched and new data collection technologies are implemented, there remains a pressing need for greater use of centralized monitoring coupled with reductions in SDR/SDV and, ultimately, greater adoption of RBM and RBQM.

With the emergence of new technologies for data collection, the continued impact of the COVID-19 pandemic, and the increasing number of partially or fully decentralized clinical trials (DCTs), the importance of risk-based monitoring (RBM) and the larger risk-based quality management (RBQM) framework in clinical trial management is increasing. RBM and RBQM focus on the detection of events or trends that impact trial quality in terms of participant safety and data integrity. In 2019, the Association of Clinical Research Organizations (ACRO) began a landscape survey of RBM/RBQM implementation in ongoing clinical trials. Initial results of this survey, representing full-year data for 2019, were reported previously. Here, we present full-year landscape data for 2020 drawn from 5,987 clinical trials ongoing at the end of 2020, including 908 new studies started that year. Of these trials, 77% implemented at least one RBM/RBQM component, an increase from 47% for studies ongoing at the end of 2019. We also observed increased implementation for three of the five RBM components included in the survey. Centralized monitoring decreased nominally in 2020 compared with 2019. Although the percentages of 2020 trials incorporating reduced source data verification (SDV) and reduced source data review (SDR) increased from 2019 to 2020, these numbers are still low considering the large percentage of trials implementing at least one RBQM component. In the current clinical trial landscape, as more DCTs are launched and new data collection technologies are implemented, there remains a pressing need for greater use of centralized monitoring coupled with reductions in SDR/SDV and, ultimately, greater adoption of RBM and RBQM.

Risk-based monitoring (RBM) is a powerful tool for efficiently ensuring patient safety and data integrity in a clinical trial, enhancing overall trial quality. To better understand the state of RBM implementation across the clinical trial industry, the Association of Clinical Research Organizations (ACRO) conducted a landscape survey among its member companies across 6,513 clinical trials ongoing at the end of 2019. Of these trials, 22% included at least 1 of the 5 RBM components: key risk indicators (KRIs), centralized monitoring, off-site/remote-site monitoring, reduced source data verification (SDV), and reduced source document review (SDR). The implementation rates for the individual RBM components ranged 8%–19%, with the most frequently implemented component being centralized monitoring and the least frequently implemented being reduced SDR. When the COVID-19 pandemic emerged in early 2020, additional data were collected to assess its impact on trial monitoring, focusing specifically on trials switching from on-site monitoring to off-site/remote-site monitoring. These mid-pandemic data show that the vast majority of monitoring visits were on-site in February 2020, but an even higher percentage were off-site in April, corresponding with the first peak of the pandemic. Despite this shift, similar numbers of non-COVID-related protocol deviations were detected from February through June, suggesting little or no reduction in monitoring effectiveness. The pre- and mid-pandemic data provide two very different snapshots of RBM implementation, but both support the need to promote adoption of this approach while also highlighting an opportunity to capitalize on the recent shift toward greater RBM uptake in a post-pandemic environment.

e18319 Background: ICH E6 (R2) has increased the level of scrutiny that we have for the data we collect in clinical trials. The emphasis is on quality-by-design with a quality management system to be incorporated and a focus on using a risk-based approach. This can be time-consuming and expensive - though the goal of this addendum is to improve quality AND efficiency, whilst ensuring patient safety and integrity of trial results. We therefore, piloted a proactive, concise and consistent method for utilizing a risk-based approach with central monitoring. Methods: Our method included 1) identifying risks within our data with 8 standard Key Risk Indicators (KRIs) across different study phases and different therapeutic areas together with 2) an off-the-shelf web-based tool for uniform and efficient review by a team of central monitors to assess which data may need more examination. These 8 KRIs are indicated in the list below, in order of the categories within the TransCelerate Risk Assessment and Categorization Tool: (S)AE rates, Enrollment Rates, Screen Failure Rates, Discontinuation Rate, Protocol Deviation Rates, Overdue Query Rate, Data Latency, and Identification of Potential Fraudulent data. Results: 15 studies were configured with the same KRIs and Visual Analytics; histograms, line- and pie-charts and data tables allowing for interactive data visualization and drill down. This represents research across different Phases 1-3 and observational studies. Based upon qualitative survey analysis from the central monitoring team 5/8 KRIs were found to be extremely valuable to focus on study quality, identifying earlier issues in study conduct for the project teams and Sponsors, while the remaining 3 were less valuable. Conclusions: We Our Risk Management team aims to increase the quality of data and ease of implementation of ICHE6 (R2) by focusing on the areas that matter the most, however identifying those areas and managing those data can sometimes be challenging. Through this innovation we have proven some core KRIs of trials that should be most closely monitored to aid decision making and will continue to evaluate to develop core oncology specific KRIs that will allow a more consistent review of data.