PACMIDS: Patient-Centered, AI-Enabled, Molecular-Informed Data Fabric for Clinical Treatment Decision Support

Introduction: The demand for comprehensive data resources has surged due to advancements in research aimed at tackling complex questions. Data integration techniques have evolved significantly, moving from the integration of various omics data types for a single patient to multimodal integration leveraging machine and transfer learning. This evolution has given rise to the concept of digital twins to facilitate in silico prediction of treatment response. Furthermore, the emergence of data fusion and data fabric concepts highlights the growing need for broader data connectivity, advanced analysis workflows, and supportive architectures. We introduce an AI-enabled, molecular data fabric that incorporates these innovative concepts to define a molecular information exchange for multimodal molecular-informed clinical treatment decision support.