Abstract B087: Feasibility study of an ex vivo functional precision medicine platform, Optim.AI™, in guiding treatment for pancreatic cancer

Abstract Background: The prognosis of pancreatic cancer is very poor, with a 5-year survival rate of less than 10%. While standard treatments are centered around chemotherapy, targeted and immunotherapy drug options are limited and are only amenable for a subset of patients. Increasing awareness and application of functional screening methods to guide patient treatment could be beneficial in indications with poor survival and response rates. Optim.AI™, a combinatorial functional precision medicine platform, has previously demonstrated clinical utility for hematological cancers and sarcoma. In this feasibility study, we explored the application of Optim.AI™ on patient-derived tumor cells in pancreatic cancer. Methods: Tumor cells were isolated from solid tissues, pleural effusion or ascites of both primary and advanced pancreatic cancer samples. Short-term patient-derived organoids were formed before combinatorial treatment with 12 drugs containing both FDA-approved chemotherapy and targeted drugs. Cell viability was quantified post-drug treatment for Optim.AI™ analysis, ranking all possible top combinatorial therapies for report generation. Results: Approximately 77% of the samples processed had sufficient viable cells to proceed with Optim.AI™ testing. Reports were successfully generated for 76% of these samples, with a mean turnaround time of 6 business days (from sample receipt to report dissemination to clinician). Z’ factor, a statistical, quality measure for high throughput screening, was demonstrated to be more than 0.5 for all reports generated, indicative of very good assays. The normalized cell viability for prior line treatments were shown to be resistant, concordant with previously observed clinical progression. Notably, top ranked combinations, with relevant citations, comprised of Gemcitabine or 5-Fluorouracil paired with targeted therapies, such as MEK inhibitors. Conclusion: This study presents Optim.AI™ as a viable clinical-decision support platform in providing alternative treatment options for pancreatic cancer. Coupled with the swift turnaround time, comparison of the top ranked therapies against the respective prior line(s) of treatments provide additional insights for subsequent line of treatment. Prospective clinical concordance analysis of Optim.AI™-guided treatments would further validate its utility in pancreatic cancer. Citation Format: Edward Kai-Hua. Chow, Masturah Mohd Abdul Rashid, Jhin Jieh Lim, Sharon Chan. Feasibility study of an ex vivo functional precision medicine platform, Optim.AI™, in guiding treatment for pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr B087.