Volume 9 Number 1 2026
Network-Driven Drug Repurposing and Natural Products in Cancer: A Systematic Review of Validation and Reproducibility
Shakharia Islam Rabby 1, Shahariar Hossain 1, Fazle Rabbi 1, Md. Fariduzzaman 1, Nayem Khan 1, Mehebin Khan Sumaiya 1, Meherab Hasan Rakib 1, Mir Nasir Ahmed Shawn 1
Advances in Herbal Research 9 (1) 1-20 https://doi.org/10.25163/ahi.9110946
Submitted: 22 July 2026 Revised: 17 September 2026 Accepted: 28 September 2026 Published: 20 September 2026
Cancer remains one of the most stubborn problems in modern medicine, and network pharmacology has, over the last decade or so, become one of the more promising ways of thinking about it differently — not gene by gene, but as a system of interacting modules that a single compound might perturb in several places at once. This review asks a fairly simple question that turns out to be surprisingly hard to answer well: when a network analysis prioritizes a natural product or an already-approved drug as a candidate cancer therapy, how much should we actually believe it? We set out, through a protocol-led systematic search of MEDLINE/PubMed, Embase, Scopus, Web of Science, and the Cochrane Library (2015 to the final September 2026 search date), to identify, appraise, and synthesize studies in which a biological network materially shaped the choice of candidate, rather than simply illustrating a decision already made. Two reviewers will screen and extract data independently, appraise computational studies against a purpose-built instrument informed by PROBAST, and apply design-specific tools to animal and clinical components; pooling will occur only where studies are genuinely comparable. Verified illustrative studies already show that network approaches can surface noncanonical kinase dependencies, metabolic vulnerabilities, subtype-specific repositioning candidates, and biologically active natural compounds — yet the wider literature still leans heavily on docking and enrichment analyses that are, frankly, presented as validation more often than they deserve to be. Our conclusion, tentative as any conclusion about an unfinished evidence base must be, is that network-driven prioritization is a genuinely useful hypothesis-generating tool, not proof of efficacy, and that its translational credibility should be judged candidate by candidate against data provenance, independent validation, target engagement, realistic exposure, and staged experimental confirmation.
Keywords: Cancer; network medicine; network pharmacology; systems pharmacology; drug repurposing; natural products; multi-omics; knowledge graph; precision oncology; systematic review.
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