The new PANGEA 2.0 algorithm uses the dynamics of four biomarkers to accurately stratify the risk of progression of smoldering multiple myeloma (SMM) to active multiple myeloma (MM).[1][2] The study collected data from 2,270 SMM patients from six international centers with longitudinal clinical and biological data for model training and validation.[1][2] Four biomarkers associated with a shorter time to progression are: an increase in M-protein ≥0.2 g/dL, an increase in the ratio of free light chains (involved:uninvolved) ≥20%, an increase in creatinine >25%, and a decrease in hemoglobin ≥1.5 g/dL.[2] The PANGEA 2.0 model outperforms established models such as 20/2/20 and IMWG with C-statistics of 0.69–0.84, even without biomarker history (C-statistics of 0.69–0.83) or recent bone marrow biopsy.[2] The training cohort included 1,031 patients with SMM, of which 231 progressed to MM.[1] PANGEA 2.0 is available as an open-access tool for individualized risk stratification.[2] The model takes into account the evolution of biomarkers, thereby improving the detection of early signs of progression compared to static criteria.[1]