An Integrated Mobile Platform for Automated Data Collection and Real-Time Patient Monitoring in Diabetes Clinical Trials

Area of Science:

• Digital health
• Clinical research informatics
• Diabetes technology

Background:

• Diabetes management requires continuous monitoring and data collection.
• Existing clinical trial platforms may lack integrated, real-time data capabilities.
• Assessing novel diabetes treatments necessitates efficient and reliable data gathering tools.

Purpose of the Study:

• To introduce a novel mobile platform designed for diabetes clinical trials.
• To enable automated data collection from continuous glucose monitoring sensors and activity trackers.
• To facilitate real-time patient status monitoring by clinicians.

Main Methods:

• Development of a modular mobile application for data logging (automatic and manual).
• Implementation of a secure cloud database for data storage.
• Creation of a web interface for clinician access and real-time patient monitoring.
• Integration of continuous glucose monitoring (CGM) and activity tracker data.

Main Results:

• The platform successfully integrates mobile app, cloud storage, and web interface functionalities.
• Automated and manual data logging capabilities were established.
• Real-time patient monitoring by clinicians is enabled via the web interface.
• Preliminary tests show encouraging results for daily-life data gathering.

Conclusions:

• The presented mobile platform offers a customizable and modular solution for diabetes clinical trials.
• It enhances data collection efficiency and facilitates real-time patient oversight.
• The platform shows promise for improving the assessment of new diabetes technologies and treatments.