Implementation of ICH E6 (R2) through identification of data risks using analytics in oncology clinical trials.

Abstract

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.