Digital pathology and imaging automation moved closer to routine workflows. A new browser-based TMA-grid tool was introduced to bring FAIR, zero-footprint de-arraying to digital pathology, targeting the hidden labor needed to turn dense tissue microarrays into usable datasets. In clinical oncology diagnostics, a study in the British Journal of Cancer assessed whether PET imaging could confirm that immunotherapy drugs reach their intended tumor targets, addressing an urgent question that complicates response prediction for checkpoint inhibitors. For bedside speed, an MRI feasibility effort reported a deep learning approach cutting multi-contrast brain MRI review time to under 100 seconds, potentially reducing the friction that slows imaging access. Together, the updates point to a pipeline where faster acquisition, standardized digital handling, and target validation biomarkers converge to reduce time-to-decision in oncology care.