Background: Immuno-Oncology (IO) therapy such as anti-PD1 and anti-CTLA4 blockade has rapidly become the standard of care in melanoma, lung, and other solid tumors. However, current biomarkers such as PDL1 expression (TPS/CPS) do not accurately predict which patients will respond to anti-PD1 therapy. There is an unmet clinical need to develop better assays to predict which cancer patients will derive benefit from anti-PD1 and anti-CTLA4 therapy. Our recently developed MicroOrganoSpheres (MOSTM) technology partitions patient tumor samples into many tiny droplets containing the patient's native tumor microenvironment, including immune cells. The patients’ MOS can then be divided across multiple test conditions, enabling the development of a functional IO assay to predict response to IO therapy. Methods: Patient tumor samples from lung, melanoma, hepatocellular carcinoma (HCC), and colorectal cancer (CRC) containing resident immune cells were partitioned into individual immunologically active MOS. Tissue digest and culture conditions were optimized to maintain native immune cell viability and functionality for 8 days, enabling immune-mediated response to immune checkpoint inhibitors to be assessed using a variety of bioanalytic methods. MOS were dosed with nivolumab/panitumumab (anti-PD1 inhibitor), atezolizumab (anti-PDL1 inhibitor), ipilimumab (anti CLTA-4 inhibitor) or an isotype control antibody (IgG). Biological response was assessed using a combination of flow cytometry, imaging, and ELISA based high-sensitivity interferon gamma (IFNy) secretion quantification. Results: Using 35 cancer specimens including lung, melanoma, ovarian and renal cell carcinoma (RCC), a functional IO assay was developed to assess cell populations within patient-derived MOS, including relevant T cell populations, and characterize IFNy secretion after exposure to immunotherapy. The assay was then validated on three patient samples with metastatic HCC, melanoma, and MSI CRC. The samples were first interrogated using the optimized immunotherapeutic assay to determine cell populations within MOS by flow cytometry, imaging including immunofluorescence labeling of cell populations, and functionality by IFNy secretion quantification, to generate aMOS IO Index (MII) with MII < 1 representing no response to therapy and MII > 1 representing response to therapy. Of the three samples, the HCC had a MII < 1 while the melanoma and CRCr had MII > 1. Each patient subsequently received either anti-PD1/PDL1 and/or anti-CTLA therapy and their response to therapy was predicted by their MII. Conclusions: These preliminary data suggest our immunotherapeutic assay represents a first-of-its-kind functional assessment that can potentially predict patient response to immune checkpoint inhibitors. Further validations of our assay are now underway in our functional precision oncology MOS IO trial.