Network Pharmacology-Guided Phytochemical Polypharmacology: Integrating Molecular Mechanisms, Experimental Validation and Clinical Translation

Network pharmacology offers a systems-level framework for prioritising potential multi-target actions of phytochemicals, but predicted network convergence alone does not establish pharmacologically relevant polypharmacology. This structured narrative review evaluates curcumin, berberine, epigallocatechin-3-gallate (EGCG), and resveratrol as representative case studies, drawing on substantial mechanistic, pharmacokinetic, and translational literature. Evidence is appraised across computational prediction, biochemical interaction, cellular pathway modulation, target engagement or functional validation, in vivo pharmacology, and human evidence, with an emphasis on exposure compatibility. Across the four compounds, overlapping effects on inflammatory, metabolic, stress-response, and growth-regulatory pathways are supported predominantly by cellular and pathway-level studies. In contrast, direct target engagement, causal contribution, and clinically achievable exposure are less consistently demonstrated. Human pharmacokinetic and tissue-exposure studies show that systemic parent-compound concentrations may differ markedly from those used in mechanistic experiments, although local exposure and metabolites can modify this relationship. Clinical studies support selected pharmacodynamic or metabolic effects but do not establish that therapeutic benefit results from the simultaneous engagement of the broad, predicted target networks. Emerging computational, experimental, and delivery approaches can strengthen hypothesis prioritisation but do not replace mechanistic validation. We propose an exposure-aware, evidence-tiered framework in which clinically meaningful phytochemical polypharmacology requires convergence of achievable exposure, target engagement, causal pharmacodynamics, and clinical outcomes.