
Major Professional Experiences
Modern medicine has been profoundly shaped by a reductionist paradigm in which disease is viewed as the consequence of discrete molecular abnormalities and treated through single-target interventions. While this framework has yielded transformative therapies for acute and well-defined conditions, it falls short in explaining and effectively treating complex diseases such as COVID-19, chronic inflammatory disorders, and neurodegeneration. Increasing evidence suggests that these conditions do not arise from isolated defects, but from system-wide reorganizations across interconnected biological networks. Here, we propose a unifying systems-level framework in which disease is conceptualized as a dynamic network state, stabilized within pathological attractor landscapes spanning immune, neural, and metabolic systems. Within this perspective, disease progression reflects transitions between stable states, rather than linear cascades of molecular events, and therapeutic efficacy emerges not from single-node inhibition but from modulating the topology of the network to drive state transitions toward health. This paradigm provides a mechanistic basis for multi-component therapeutics, including traditional Chinese medicine, whose distributed, low-dose interventions can induce system-level reconfiguration and restore physiological attractors. By reframing disease and therapy through the lens of attractor dynamics, we offer a conceptual bridge between reductionist biology and holistic medicine, opening new avenues for understanding, predicting, and controlling complex human diseases.
Dr. Yuh-Chiang Shen is dedicated to advancing Innovative Traditional Chinese Medicine (iTCM) and modernizing herbal therapeutics through a systems-based translational framework. He established the “Evidence Chain” in conjunction with the CMCTC (Clinical-driven Modernization of Chinese Traditional Medicine) model, creating a closed-loop pipeline that connects bedside observations, mechanistic validation, and real-world implementation.
His work moves beyond the conventional “single-cause, single-target” paradigm by proposing a systems medicine perspective in which disease is defined as a dynamic state. Within this framework, complex diseases are understood as stable configurations—attractor states—within multi-layered biological networks (neural, immune, and metabolic). Disease arises when the system shifts into a pathological attractor, while therapy is conceptualized not as elimination, but as guiding the system across critical transitions back to a healthy attractor.
During the COVID-19 pandemic, Dr. Shen led the development and mechanistic elucidation of NRICM101 and NRICM102. Through integrated multi-omics, RNA sequencing, and animal models, his work demonstrated that these multi-component herbal formulations exert therapeutic effects not through single targets, but via multi-component synergy and network reconfiguration, modulating key inflammatory and immune pathways (TLR, JAK/STAT, PI3K/AKT, NETosis). This systems-level modulation effectively redirects disease trajectories, significantly reducing disease severity and mortality.
At the mechanistic level, his research further characterizes complex diseases—including COVID-19, COPD, and neurodegenerative disorders—as critical state transition phenomena across interconnected biological networks. His approach emphasizes multi-target intervention, network regulation, and attractor modulation, integrating AI and network pharmacology to reveal how herbal formulas produce emergent therapeutic effects even at low concentrations through system-wide reorganization.
Dr. Shen’s team has established an integrated translational ecosystem encompassing herbal design, quality control (CMC/HPLC), mechanistic studies, animal models, and clinical and real-world data (RWD). By applying methods such as propensity score matching, his work elevates RWD to near-RCT-level evidence, while introducing system-state transition as a novel clinical efficacy metric beyond single biomarkers.
His research further demonstrates that diverse diseases share common underlying inflammatory and neuro-network dysregulation, corresponding to similar pathological attractor structures, thereby enabling cross-disease, scalable translational models.
Dr. Shen has been named among Stanford University’s top 2% of scientists worldwide for five consecutive years (2020–2025). His work not only strengthens the scientific foundation of TCM, but also pioneers a new medical paradigm centered on attractor dynamics, integrating Eastern holistic philosophy with modern systems science to establish a globally competitive model of translational medicine with clinical, industrial, and societal impact.
Publication (selected)
專利佈局
Published Papers
NCBI PubMed : Yuh-Chiang Shen (Please click!!)