Precision Oncology in Northern Germany – Integrating Multi-Omics and AI to Support Evidence-Based Molecular Tumor Boards

The expanding availability of multi-omics profiling and advances in artificial intelli-gence (AI) and machine learning (ML) are changing precision oncology. Molecular testing strategies such as longitudinal liquid biopsy assessment, germline variant analysis, and the evaluation of tumor-infiltrating clonal hematopoiesis (TI-CH) are gain-ing attention, given their potential to inform treatment decisions from surveillance through therapy selection. In 2025, during a NORD (Northern Oncology, Research and Development) workshop on "Precision Oncology", stakeholders from three Northern German university hospitals exchanged insights on the impact of tumor heterogeneity and the tumor microenviron-ment, approaches for multi-layer data integration, and strategies to accelerate transla-tion using innovative clinical trial designs. Building on this discussion, participants evaluated how the integration of multi-omics data, AI and ML into molecular tumor board (MTB) workflows could enhance decision-making, as well as the challenges as-sociated with implementing these tools in routine clinical care. The workshop thereby not only identified key opportunities and obstacles but also formulated recommenda-tions on how these tools can be stepwise integrated into existing workflows to generate the evidence required for their implementation in clinical practice. This review connects expert perspectives with targeted literature to outline how these emerging methods advance precision oncology. It further identifies the technical, struc-tural, and clinical requirements for their implementation in clinical use, and highlights how they can improve the quality, speed and accessibility of MTB recommendations.