A Systemic Pathological Network Model and Combinatorial Intervention Strategies for Alzheimer's Disease

Alzheimer's disease (AD) persists as a paramount challenge in neurological research, characterized by the pathological hallmarks of amyloid-$\beta$ (A$\beta$) plaques and neurofibrillary tangles composed of hyperphosphorylated tau. This review synthesizes the evolving understanding of AD pathogenesis, moving beyond the linear amyloid cascade hypothesis to conceptualize the disease as a cross-talk of intricately interacting pathologies, encompassing A$\beta$, tau, and neuroinflammation as the foundation of phase-adapted pathological network model. This evolving pathophysiological understanding parallels a transformation in diagnostic paradigms, where biomarker-based strategies such as the AT(N) framework enable early disease detection during preclinical or prodromal stages. Within this new landscape, while anti-A$\beta$ monoclonal antibodies (e.g., lecanemab, donanemab), represent a breakthrough as the first disease-modifying therapies, their modest efficacy underscores the limitation of single-target approaches. Therefore, I explore the compelling rationale for combination therapies that simultaneously target A$\beta$ pathology, aberrant tau, and neuroinflammation. Looking forward, I emphasize emerging technological platforms such as gene editing and biophysical neuromodulation in advancing precision medicine. Ultimately, the integration of early biomarker detection, multi-target therapeutic strategies, and AI-driven patient stratification charts a promising roadmap toward fundamentally altering the trajectory of AD. The future of AD management will be defined by preemptive, biomarker-guided, and personalized combination interventions. Keywords: Alzheimer's disease, amyloid-$\beta$, tau pathology, neuroinflammation, combination therapy, multi-target therapy, precision medicine, biomarkers