Abstract SY04-02: Clinical applications of cancer digital twins

Abstract Digital twins for cancer tumors are emerging as a transformative tool in oncology to enable a more personalized and dynamic approach to cancer treatment. In this talk, I will showcase a growing library of mechanistic, data-driven computational models, focused on the signaling pathways within tumor cells and their microenvironment for various types of cancer (namely triple-negative breast cancer, non-small cell lung cancer, melanoma and glioblastoma). These computational models are mechanistically interpretable, enabling us to understand and anticipate emergent resistance mechanisms and to design patient-specific treatment strategies that counteract the forces of clonal selection driving treatment relapse, to improve outcomes for patients with hard-to-treat cancers. Citation Format: Jasmin Fisher. Clinical applications of cancer digital twins [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr SY04-02.