PROJECT SUMMARY High-dimensional molecular profiling, including genomic sequencing and digital pathology, has revolutionized our understanding of cancer and has led to the identification of multiple new targets and biomarkers. However, barriers impede unlocking the full potential of these data because most ‘omic data generated from National Cancer Institute’s National Clinical Trials Network (NCTN) clinical trials are decentralized, with data housed at a variety of sites and analyses taking place locally. To overcome these barriers for Alliance NCTN cooperative group trials, in 2020 we established A-STOR: Alliance Standardized Translational Omics Resource, a secure, HIPAA-compliant centralized repository of raw, and processed genomic and pathology image data from Alliance clinical trials, with standardized genomic data harmonization to facilitate cross-study analyses. In this proposal (a supplement to the Alliance U10 grant), we aim to realize the potential of A-STOR for artificial intelligence (AI)/machine learning (ML) modeling by rapidly expanding our existing infrastructure to: host data from over a dozen existing or ongoing Alliance/NCTN clinical trials (Aim 1), optimize infrastructure for cloud-based AI/ML analyses including engagement with and feedback from AI/ML applications (Aim 1-2), ensure FAIR principles in developing a unified clinical and adverse event (AE) data dictionary to facilitate clinical data harmonization (Aim 2), and complete an already-approved pooled multi-modal ML-based predictor as a pilot study (Aim 3). The impact of these aims will collectively capitalize on the expertise of Alliance A-STOR Co-Chairs Dr. Daniel Stover (clinical informatics, genomics) and Dr. James Blachly (computational biology, computer science), to optimize foundational infrastructure, clinical/AE harmonization to facilitate data reuse as part of AI/ML efforts, and cloud- based AI/ML compute optimization for data generated through Alliance NCTN cancer clinical trials.