Aims and Scope

Traditional Chinese Medicine (TCM), refined over millennia, offers a unique holistic and dynamic perspective on managing complex diseases. Central to its philosophy is the concept of Zheng (证, syndrome)—a systemic pattern of disharmony reflecting a patient's unique pathophysiological state that guides personalized treatment. However, the modernization and global integration of TCM face a fundamental challenge: the paradigm mismatch between its macroscopic, syndrome-based diagnostics and the microscopic, target-centric focus of modern biomedicine. This gap, compounded by the multi-component, multi-target complexity of TCM herbal formulas (Fufang, 复方), has created a "black box" that obscures mechanistic understanding and robust preclinical evaluation.

Organoid technology has emerged as a transformative platform poised to bridge this critical gap. As three-dimensional, self-organizing, and physiologically relevant models, organoids recapitulate key structural and functional features of human organs. Crucially, patient-derived organoids (PDOs) capture inter-individual variability, echoing TCM's emphasis on personalized care. Organoids provide an unprecedented experimental system to model the dynamic, multi-scale states defining TCM syndromes, offering the potential to translate holistic concepts—such as "Qi deficiency" (气虚) or "Blood stasis" (血瘀)—into measurable biological phenotypes, or "biological fingerprints." In this sense, organoids function as a 'Rosetta Stone'—just as the ancient artifact enabled the deciphering of Egyptian hieroglyphs, organoid technology now enables the translation of TCM's holistic principles into the molecular vocabulary of modern medicine.

At a deeper theoretical level, this Special Issue is grounded in the "State-Target Co-regulation" (态靶辨治) framework—a novel integrative paradigm that synthesizes TCM's holistic worldview with cutting-edge precision medicine. This theory posits that disease emerges from dysregulated "states" (态)—dynamic, multi-dimensional biological configurations spanning cellular, tissue, and systemic scales—that can be modulated through coordinated modulation of multiple "targets" (靶). Organoids, as living biointerfaces, are ideally suited both to recapitulate these disease states and to serve as platforms for discovering state-modulating interventions.

We invite submissions of cutting-edge original research, reviews, perspectives, and methods papers that integrate organoid models with multi-omics profiling, network pharmacology, high-throughput screening (HTS), high-content imaging (HCI), and AI-driven computational analysis. By fostering this interdisciplinary integration, this Special Issue aims to revolutionize the scientific foundation of TCM, accelerating the journey from ancient empirical wisdom to modern mechanistic understanding, and ultimately delivering safer, more effective, and personalized therapeutic strategies for global health challenges.

Topics of Interest

This special issue invites submissions across the intersection of organoid technology and TCM modernization. We particularly encourage submissions in the following strategic areas:

• Modeling TCM Syndromes: Foundational Organoid Platforms and "Syndrome-in-a-Dish" Validation
• Deciphering TCM Mechanisms: Systems Pharmacology, Multi-Omics, and "State-Target" Co-regulation
• Drug Discovery: High-Throughput Screening and Efficacy Evaluation of TCM Formulas and Natural Products
• Safety Assessment: Toxicology Evaluation and ADMET Profiling of TCM
• Digital TCM: AI-Driven Analysis of Organoid Imaging and Multi-Omics for Quantitative Syndrome Modeling
• Clinical Translation: Patient-Derived Organoids (PDOs) for TCM Personalized Therapy and Precision Medicine
• Preventive TCM ("Zhi Wei Bing"): Disease Interception and Reversion of Precancerous Lesions

Guest Editor

Wei Deng (Institute of Emergency and Critical Care Medicine, Shanghai University of Traditional Chinese Medicine, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine)

E-mail: dengwei82@vip.163.com

Submission deadline: Dec. 31, 2026