Abstract Previously preclinical models for customized drug screening and precision oncology are being developed to replace animal models. Advances in biocompatible organoid technology have made it possible to culture cancer organoids from human tumor tissues. Cancer organoids are easy to proliferate, and large-scale drug screening platforms can be developed in that they can reproducibly repeat experiments with various concentrations of drugs. In this study, we developed automated extracellular matrix integrated, three-dimensional, patient-derived cell spotting technology and pillar-based cancer organoid culture system for anticancer drug screening platform as a preclinical model which able to contribute for prediction of therapeutic responses and selection of optimal next line anticancer drugs. In case of ovarian cancer, about 70-80% of patients are firstly diagnosed, but their 5-year survival rate is still under 50%. To increase the 5-year survival rate, raising therapeutic responses is urgently needed by effective drug treatment rather than standard therapy. For drugs selected through a drug screening platform to be applied to actual clinical practice, standard test methods must be set up, and clinical results and organoid-based treatment responses must be clearly compared and verified. For validation above, we confirmed the organoid on pillar-based drug testing platform by using surgical specimens from 109 ovarian cancer patients from SMC (Samsung medical center). Primary cells with extracellular matrix spotted and cultured on 384 pillar plates by ASFA spotter (MBD Inc.). After organoid formation on pillars, anticancer drug screening was performed for 14 drug combinations using cancer organoids derived from the ascites of patients. Cell viabilities and drug responses were calculated by ATP measurement and staining of intracellular Calcein then. Particularly in this study, parallel with drug treatment, organoid growth rate was measured by comparing the average areas, processed by ASFA cell analyzer (MBD Inc.), of organoids at drug treatment and termination day. Finally anticancer drug sensitivity index was calculated by combination of the drug response of AUC and respective organoid growth rate, then it was verified by matching with the clinical responses of 1st chemotherapies after surgery. As a results, the drug susceptibility index was predicted patients of recurrence within 6-month after 1st chemotherapy by our drug screening platform with increased sensitivity and specificity. This anticancer drug screening platform raised the recurrence prediction about 90% compared to existing drug sensitivity index such as IC50 or AUC, and through this, this platform could contribute to precision medicine in ovarian cancer patients. Therefore, it can be preclinical model used to screen the optimal drug for customized treatment using patient-specific individual organoids. Citation Format: Hye Ryeong Jun, Sung Hun Ju, Jung Eun Kim, Dong Woo Lee, Bosung Ku, Joseph Noh, Jeogn-Won Lee, Hyun Ju Kang, Jin-Ku Lee. Organo-on-pillar based anticancer drug screening platform for ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 762.