The Clinical Systems Biology Platform of Shanghai Clinical Research and Trial Center is an innovative research platform built by the team led by Professor Zeng Rong, one of China’s pioneers in proteomics and systems biology, based on the framework of a new research-oriented hospital. Committed to bridging cutting-edge scientific and technological advances with clinical research demands, the platform develops intelligent analytical systems for personalized dynamic molecular networks based on quantitative molecular network data from large-scale population cohorts. It provides systematic support for clinical research and high-quality medical services. Relevant research findings have been published in top-tier journals including Nature Medicine, Cancer Cell, Cell Metabolism, and Cell Genomics.
Through a joint laboratory established with the National Facility for Protein Science in Shanghai, the platform further focuses on frontier technologies for dynamic protein research in complex biological systems and their clinical translational applications. In 2025, the joint laboratory officially launched the Systems Health & Disease (SHD) Database. Built upon a rigorous systems biology framework, the SHD Database serves as a large-scale population multi-omics resource platform. It breaks through the limitations of single-layer and single-population data resources, supports in-depth mining and integration of multi-omics data, and lays a solid data foundation for the development of AI-powered multimodal diagnosis and treatment support systems.
Platform Mission：To provide hospital-wide translational services centered on in-depth multi-omics detection and analysis for large-scale population cohorts.
Limitations of Traditional Research Models：Traditional hypothesis-driven cellular and animal studies feature linear and partial exploration approaches. Restricted by the complexity of real-world clinical scenarios, their research outcomes show limited applicability and accuracy in clinical diagnosis and treatment practices.
Core Development Approach：Adopting a data-driven research paradigm that realizes closed-loop innovation: from clinical population cohorts to clinical diagnosis and treatment.
Development Goals：To systematically collect clinical samples from all departments of the hospital, generate high-throughput, in-depth omics molecular data via advanced omics technologies, and build a million-scale molecular data asset repository for systematic health and disease research.
1. Large-Cohort High-Throughput Deep Proteomic and Metabolomic Profiling
—High-depth Proteomics: Enables high-throughput, highly reproducible and precise proteome quantification in large clinical cohorts, as well as sensitive deep profiling of low-abundance proteins.
—Broad-spectrum and Targeted Metabolomics & Lipidomics: Covers a wide range of molecules including lipids, endogenous metabolites, nutrients, and environmental pollutants.
2. Clinical Data Asset Construction and End-to-End “Cohort-to-Translation” Services
—Adhering to the data-driven research paradigm, the platform provides one-stop translational research support for clinical departments and prospective cohort studies.
—It assists departments in standardized preprocessing of clinical samples and high-quality data generation, supporting the construction of a million-scale molecular data asset for systematic health and disease research.
—Clinical Translation and Solution Design: Delivers full-link collaborative services covering clinical problem formulation, cohort omics design, experimental detection, algorithm mining, and clinical validation, accelerating the translation and clinical implementation of high-level research outcomes.
