Abstract 6298: The first fully automated, integrated workflow between a small animal imaging tool and animal study management software improves the accuracy, reproducibility, and efficiency of small animal imaging studies

Abstract Preclinical imaging systems and electronic data capture (EDC) technologies are transforming biomedical research and drug discovery by offering powerful, time-saving tools for oncology study data acquisition, analysis, and management. Advanced imaging modalities, such as bioluminescence, fluorescence, CT, MRI, and PET imaging, allow researchers to non-invasively visualize and quantify biological processes in small animal models. These systems support longitudinal studies of disease progression, therapeutic efficacy, and molecular mechanisms, aiding novel drug development while minimizing animal usage through precise data collection. Companies like Analytik-Jena provide high-resolution small animal imaging solutions that help researchers gain deeper insights into biological phenomena. Complementing these innovations, EDC systems like Studylog Animal Study Software streamline preclinical workflows by automating data collection, validation, and analyses. Together, preclinical imaging and EDC technologies drive innovation in biomedical science by enabling robust and efficient data capture. However, before this writing, no integration between preclinical imaging and EDC technologies existed, forcing researchers to rely on a heavily manual process of imaging data association with study animals to generate statistical and graphical results This manual process is fraught with a variety of error types and is extremely time-consuming. Furthermore, access to results and original animal images in the context of the study is absent altogether. This paper reports on the first automated integration of preclinical imaging and animal study workflow software available. Having tools that enable seamless tracking of the animals used for the collective small animal imaging study processes, such as substrates administered, incubation time points, anesthesia records, image collection, animal identification association, -including region of interest (ROI) determination, and tracking—is crucial to improving the accuracy, reproducibility, and efficiency of these studies. Equally important is the accurate transfer of this data into a database, ensuring the integrity and long-term accessibility of study data and results. The novel integration feature enables seamless communication between Studylog and VisionWorks by exchanging data in a standardized format via local methods or internet-based APIs. This allows scientists to initiate workflows in Studylog, process imaging and analysis in VisionWorks imaging software, and then send results back to Studylog with a single click, supporting both local and remote collaboration. Citation Format: Sean R. Gallagher, Meng Yang, Eric Ibsen, Antonio Boccia, Madalin Florescu, Qi Wang, Neil Chang. The first fully automated, integrated workflow between a small animal imaging tool and animal study management software improves the accuracy, reproducibility, and efficiency of small animal imaging studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6298.