From Reads to Reports: A Vision for a GFM-Powered Genomic Diagnostic Platform

Microbiome sequencing offers significant potential for advancing clinical diagnostics, but its adoption is hindered by challenges in data processing, standardization, and the translation of complex genomic data into actionable clinical insights. The GenDAI project addresses these challenges by developing a novel, integrated medical diagnostics platform that leverages Artificial Intelligence (AI), powered by Genomic Foundation Models (GFMs), to accelerate and improve the analysis of microbiome data. The platform's primary goal is to provide a fully automated, reproducible, and compliant end-to-end solution, from data ingestion to clinical reporting, to support personalized medicine, with an initial focus on Inflammatory Bowel Disease (IBD). This paper presents an overview of GenDAI's vision, outlining its user-centered methodological approach and the conceptual architecture of its core components. The architecture integrates four key pillars: (1) a fully automated and auditable diagnostics workflow, (2) a secure and compliant cloud platform for long-term data management based on Open Archival Information System (OAIS) and Findable, Accessible, Interoperable, Reusable (FAIR) principles, (3) an advanced AI engine for biomarker discovery using GFMs, and (4) interactive, usercentered reporting tools designed to enhance explainability and clinical trust. By providing a holistic and ethically-grounded framework, GenDAI aims to bridge the gap between advanced genomic research and practical clinical application.