A4.2 Optimizing Clinical Trials with Real-Time Study Status Reporting: A Python-based Desktop Application

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Clinical data science and analytics are critical to the success of clinical trials. This abstract describes a desktop application for reporting study status using Python and the PyQt6 library. This application enables real-time analysis and visualisation of study health metrics in both tabular and graphical formats, including page status (Data Entry, SDV Status, PI Signatures and their percentages of completion/pending), Protocol Deviation, and Query status (open & answered queries with ageing ranging from 5 days to >50 days with their respective Marking Groups). Additionally, it allows study teams to quickly identify areas of concern or progress and make informed decisions.Moreover, this application is specifically designed to reduce financial burden by saving time required in generating study metrics with minimal human intervention. These metrics are at times required weekly for ongoing studies or on a daily basis during significant milestones such as futility analysis, database lock, site closures, or subject transfers.The designed interface is user-friendly, with just three clicks to upload the required reports for analysis. After this, the program analyzes reports in milliseconds and displays the results in tabular and graphical formats, such as pie charts. Furthermore, it provides the option to export data in PDF format and create emails directly along with the data populating in the email body. Here, users can create a new email with the data in the email body, including a date stamp just by clicking the create email push button. Also, they can manually update the recipient's email address, eliminating the need for data copying and pasting and minimizing manual error.This programme has been rigorously tested with multiple data scenarios to ensure accuracy and speed. Also, this application shortens the time and effort needed for data analysis and reporting.In conclusion, the Study Status Dashboard provides an easy-to-use interface for clinical data analysis and visualization. The dashboard's speed, accuracy, and accessibility lessen the financial burden while increasing efficiency in clinical data analysis and reporting. The quick ability of this application to identify areas of concern or progress and make informed decisions can have a significant impact on clinical trial success.