Abstract: AbbVie is a global, research driven, bio-pharmaceutical company tackling the world’s toughest health challenges. As a company we have over a hundred ongoing clinical trials at any given time. With such a large scale of clinical trials in conduct, there is a dire need to develop and deploy data and statistics driven solution to ensure clinical data quality. The Clinical Data Reviewer (CDR) is a new, yet integral role within Data and Statistical Sciences (DSS) dedicated to anticipate, troubleshoot, and resolve data integrity issues. Traditionally, data management relied heavily on simple edit checks and manual Excel listings. The release of ICHE6 R2 guidelines for good clinical practice set a new and higher standard of scientific quality for conducting, recording, and reporting clinical trials. This stressed the need for centralized monitoring and aggregate data review. The CDR role utilizes advanced statistical methodologies to perform data review and enable data-driven decisions during the life of a clinical trial. CDRs operate by the following principle: The integrity of the research depends on the integrity of the data. By exploring data trends and behaviors that cannot be captured in programmed edit checks, we ensure the broader integrity of the data. The team leverages TIBCO Spotfire, a data visualization tool, to create generic (demographics, adverse events, pharmacokinetics) and study specific (Endpoints, ePRO, drug accountability) visualizations, at a subject, site, or study level, to identify potential issues. These include, but are not limited to, scatter plots, box plots, heat maps, cross tables, pivot tables, or a combination of the above. CDRs also use R, a traditional statistical programming tool, to wrangle or analyze data and perform more complex checks across multiple data sources. Currently we are exploring univariate, unsupervised Machine Learning techniques to streamline automation of outlier and anomaly detection in Clinical Trials. Together, these techniques support a holistic review of clinical data and ensure the highest quality database from study start up to final lock.