Abstract
Timely, consistent and integrated access to clinical trial data remains one of the pharmaceutical industry’s most pressing needs. As part of a comprehensive clinical data repository, we have developed a data warehouse that can integrate operational data from any source, conform it to a canonical data model and make it accessible to study teams in a timely, secure and contextualized manner to support operational oversight, proactive risk management and other analytic and reporting needs. Our solution consists of a dimensional relational data warehouse, a set of extraction, transformation and loading processes to coordinate data ingestion and mapping, a generalizable metrics engine to enable the computation of operational metrics and key performance, quality and risk indicators and a set of graphical user interfaces to facilitate configuration, management and administration. When combined with the appropriate data visualization tools, the warehouse enables convenient access to raw operational data and derived metrics to help track study conduct and performance, identify and mitigate risks, monitor and improve operational processes, manage resource allocation, strengthen investigator and sponsor relationships and other purposes.
Highlights
One of the main factors driving the inefficiencies in the current clinical development model is the lack of convenient and integrated access to clinical trial data
In the Xcellerate suite, access to the metrics and KPI/KQI/KRIs stored in the operational data warehouse (ODW) is provided mainly through the Xcellerate Study Reporting, Portfolio Reporting, Risk Review and clinical research associate (CRA) dashboards
The dashboard is organized into several views, each reporting key metrics related to the performance of clinical development functions, sites, geographical regions or combinations thereof
Summary
One of the main factors driving the inefficiencies in the current clinical development model is the lack of convenient and integrated access to clinical trial data. Clinical trial data are typically collected through multiple systems developed by different vendors using different technologies and data standards. These data fall into two main categories: (i) operational data, which are used to monitor the progress and operational health. The CTMS is a core transactional system that is used to manage sites, monitoring visits, site issues, trip reports and various other study metrics and milestones. While certainly useful, these efforts have focused mostly on minimizing duplicative data entry rather than enabling downstream analytics [1, 2]
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