Abstract 1293: PMed-TRIAL database: an efficient and intelligent data integration platform shaping the future of drug development

Abstract With the rapid advancements in artificial intelligence (AI) and big data technologies, the fields of precision medicine and drug development have entered a transformative data-driven era. Leveraging years of accumulation and expertise, LIDE launched the PMed-TRIAL Database in 2023. Through continuous iteration and expansion, PMed-TRIAL has evolved into a comprehensive data integration and query platform, encompassing PDX (Patient-Derived Xenograft), CDX (Cell Line-Derived Xenograft), Syngeneic models, and Conditional Reprogramming Cell Lines. The platform enables efficient data retrieval and intelligent integration, providing indispensable support for clinical and drug research in this new era. The database currently hosts nearly 1, 800 PDX models, making it one of the largest PDX repositories worldwide. These models integrate and standardize a wide range of key datasets, including clinical information, treatment history, growth curves, SOC (standard of care), and H&E (hematoxylin and eosin staining) results, among others, which greatly facilitates the filtering and selection of suitable models for drug research. Furthermore, the associated whole-exome sequencing (WES) and RNA sequencing datasets provide critical evidence for drug mechanisms research. In addition to standard PDX models, the database also includes induced drug-resistance models, providing an essential resource for studying drug resistance mechanisms and screening drugs to overcome resistance. In addition to PDX models, the PMed-TRIAL Database incorporates information on Patient/PDX-derived conditional reprograming cell lines, PDXO (PDX Derived Organoids), Syngeneic models, and CDX models. This expanded scope addresses the multi-faceted demands of drug development, accelerating research timelines and enhancing the efficiency of the drug discovery process. Most importantly, the PMed-TRIAL Database standardizes and efficiently integrates diverse model datasets. The accumulation of large-scale, high-quality data not only streamlines current research efforts but also lays the groundwork for advancing AI applications in drug development in the future. By bridging innovative technologies with comprehensive data resources, PMed-TRIAL empowers researchers to unlock new possibilities in precision medicine and therapeutic innovation. Citation Format: Xinlei Chen, Youbing Guo, Loc Van, Josh Caggiula, Danyi Wen. PMed-TRIAL database: an efficient and intelligent data integration platform shaping the future of drug development [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 1293.