GEN-RWD Sandbox Ecosystem for Privacy-Preserving Data Sharing in Healthcare Research: The Processor Module

Abstract

Recent innovations in computer science and informatics are driving the integration of AI into modern healthcare, extending its applications to medical sectors previously reliant on human expertise. Creating robust and clinically relevant AI models requires extensive data, which can be challenging to gather, particularly when dealing with rare diseases. Data sharing among healthcare entities can address this issue, but legal, privacy, and data ownership concerns hinder such approach. To foster data sharing, in this paper we propose the GEmelli GeNerator - Real World Data (GEN-RWD) Sandbox, that provides a secure environment for data analysis without compromising sensitive medical data. This modular architecture serves as a research platform for various stakeholders, including clinical researchers, policymakers, and pharmaceutical companies. Au-thorized users submit research requests through the GUI, which are processed within the hospital, and the results can be accessed without revealing the original clinical data source. In the context of this paper we present GEN-RWD Sandbox's architecture module in charge of executing the analysis requests, the Processor. Processor's code is openly shared as the GSProcessor <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R$</tex> package available at https://gitlab.com/benedetta.gottardelli/GSProcessor.

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