Risk-Based Monitoring (RBM) and Data Quality Analysis (CSM) of Clinical Trials using

1. Risk-Based Monitoring (RBM) and Data Quality Analysis (CSM) of Clinical Trials using www.i-review.com

2. JReview Developed from day 1 as a Clinical Research application • Understands ‘patient’, ‘baseline’, ‘endpoint’, etc. • Integrated with many clinical data sources • Dynamic multi-study pooling • Built-in ‘patient identification/drill down’ • Patient review tracking • Many clinical data specific graphics, tabulations, profiles, risk assessments, etc. including defining critical data • Built in codelist/sas format awareness • SAS/R program integration • Patient Narratives • Works with CDISC as well as Legacy Data formats • Risk-Based Monitoring & Data Quality Analysis (CSM)

3. Special Graph Types for Clinical Data • Multiple scientific, clinically relevant graph types for clinical data visualization – with patient identification built in • Baseline/Endpoint plot • Shift Plot • Benefit-Risk Plot • Napoleon’s March Plot • Hy’s Law Plot, Composite Hy’s Law • Time-to-Event Plot • Forest Plot • Dot Plot • Box Plot • Tree MapSunburst Plot • Trellis Plot • …

4. Patient Profiles • Time-oriented (days on drug) graph display of user selected parameters • Dynamically choose categories and items to include • Drilldown to selected data of interest • Graphical or tabular (formatted) output • Export to Excel, HTML, PDF • Optional batch report option

5. JReview – Data Anomaly Detection • Companies have been using JReview for data anomaly detection for many years – using clinical data visualizations, exception reporting, etc. • Since we already had access to the clinical data for studies – we thought it would be good to add specific RBM definition and visualization capabilities to JReview 10 (2014) • Later – realizing that the RBM capabilities address data issues we thought of (supervised), we researched and developed an additional ‘unsupervised’ data quality analysis in JReview 13.1 (2018)

6. JReview 10 Out of the box Analytics support for Risk Based Monitoring • Centralized monitoring teams can define key risk categories and indicators from all clinical & operational source data available, set thresholds, and specify suggested actions • The JReview RBM Data Browser allows for the design of aggregated risk-based monitoring reports which can be scheduled in regular intervals to push monitoring activity plans out to site monitors/CRAs • Periodic ‘risk factor’ batch execution • Visualization of risk evolution by site/country/region based on multiple risk indicators & -categories

7. RBM Risk Indicator Definition Key Risk Indicators, thresholds, & suggested actions Definition within JReview with test run  scheduled periodic execution

8. RBM Data Browser Risk Indicator Result Visualization by site, country, or region - subset by attributes - interactively sort any columns for site ranking

9. Site Distribution Over Time Site Distribution (Box Whiskers) over time – for selected site & RBM rule results table

10. RBM Treemap Site – Risk Indicator weight visualization – Tree Map visualization

11. JReview 13.1 • Data Quality Analysis – ‘Unsupervised Analysis’ Automated data quality analysis Wide variety of analyses in background Review results interactively High level combined results (global score) -> detail results

12. Global Scores – Tree Map

13. Data Quality Checks – Categories & Weight

14. Other Info – Geographic Region, SAE, Discontinuation, etc.

15. Tables & Items to be included in Analyses

16. Duplicate Patient Identification Information

17. Overview of checks Methods where p-value is part of the result digit preference correlation check variance distribution check categorical variable check p value combination Methods that raise flags as results duplicates check inliers integer check outliers SAE check missing value check baseline check