Newly-launched database offers easier access to diverse tumor models and unveils the path to pharmaceutical breakthroughs
ChemPartner, a global leader in drug discovery and development services, today announced the launch of its long-awaited Biology Database. This innovative platform serves as a centralized hub, empowering ChemPartner’s clientele with seamless access to a wealth of information on the organization’s cutting-edge preclinical platforms. The database includes 800+ tumor models, 30+ cancer types, 20,000 genes, 2,300+ pathways, 1,800 SoC data from literature (500 internal), and 30+ analytic modules.
ChemPartner’s renowned biology and pharmacology department, known for its vanguard oncology, immunology, CNS, and metabolic services, has curated an extensive collection of in vitro and in vivo models. The database boasts over 2,000 biochemistry assays, 800 cell lines, 500 patient-derived xenograft (PDX) models, 350 cell-derived xenograft (CDX) models, and 50 syngeneic models. Each model is meticulously characterized with comprehensive data encompassing genomics, pharmacology, histopathology, and relevant clinical information.
Cell Line Models – ChemPartner Biology Database
To ensure a smooth and efficient rollout of this substantial volume of data, the database will be introduced in stages. We are delighted to announce that the first stage, featuring cell line data, is now live on https://database.chempartner.com/. Subsequent stages will include CDX, syngeneic, and PDX models, followed by biochemistry data.
The Biology Database, a flagship online collaborative platform, prominently features the Tumor Model Database. This revolutionary resource offers an array of features, including:
Unified Data Hub: Integration of dispersed tumor model data into a centralized database for efficient management and retrieval, simplifying user access to diverse tumor models.
Detailed Annotations: Each model is accompanied by intricate annotations including genomics, pathology, and pharmacology data, enabling rapid understanding of model characteristics and suitability for specific research needs.
Rapid Search and Filtering: Multidimensional search and filtering capabilities empower researchers to swiftly locate models based on cancer type, genomic features, drug sensitivity, and more.
Data Analysis and Mining: Robust tools facilitate tasks like drug mechanism analysis and biomarker discovery through differential gene expression and drug sensitivity analyses, supporting informed research decisions.
Data Visualization: Intuitive charts, statistics, and visualization tools present complex data clearly and concisely, aiding in model selection and analysis.
Dr. Lilly Xu, President of Shanghai ChemPartner, expressed enthusiasm about the launch saying, “We are excited to provide our customers with access to this powerful new resource. This comprehensive database will make it easier for our customers to find and use the right models for their research, propelling drug development towards new heights with better precision, efficacy, and efficiency.”
