Precision medicine aims to improve effective treatment selection based on patient-specific features such malignant genomic or transcriptional alterations. Functional precision medicine approaches, which include ex vivo phenotypic drug response data, can provide additional information to further improve individualized treatment selection. We have previously reported the clinical feasibility of a combinatorial functional precision medicine platform, QPOP/Optim.AI™, to accurately identify both effective and resistant treatment options in non-Hodgkin lymphoma (NHL) (Science Translational Medicine, 2022), acute myeloid leukemia (AML) (Cancer Medicine, 2024) and soft tissue sarcoma (npj Precision Oncology, 2025).
This study now explores the real-world clinical application of Optim.AI towards predicting drug sensitivity and resistance across a range of both hematological and solid cancers in a Singapore Ministry of Health (MOH) licensed clinical laboratory (L/23I0025/CLB/002/242). The work presented here provides evidence of the broad applicability of combinatorial functional precision medicine approaches in oncology.
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