Background: Driven by artificial intelligence (AI) and genomics, personalized medicine (PM) is rapidly expanding. Mapping its conceptual structure through co-word analysis identifies research trends, thematic gaps, and priorities. This study mapped the conceptual structure and thematic evolution of PM in Iran from 2005 to 2025 using Web of Science (WoS) data.
Methods: Keyword co-occurrence and network analysis were performed on 623 WoS-indexed documents. Cluster analysis in VOSviewer and strategic diagrams in Excel identified thematic sub-domains and their relationships.
Results: Cluster analysis revealed nine distinct thematic clusters: (1) AI and machine learning in medical imaging and diagnosis; (2) gene editing, omics technologies, and the microbiome’s role in treatment; (3) personalized medicine and pharmacogenomics; (4) biomarkers and liquid biopsy in cancer diagnosis; (5) nanomedicine, biosensors, and targeted cancer therapy; (6) tissue engineering, regenerative medicine, and novel drug delivery systems; (7) early detection and management of chronic, inflammatory, and metabolic diseases; (8) nanoparticles, epigenetics, and integrative medicine approaches, including traditional medicine and digital health; and (9) cancer immunotherapy and tumor microenvironment analysis.
Conclusion: Personalized medicine in Iran has a dynamic, interdisciplinary, and evolving structure. Pharmacogenomics serves as the key infrastructure and driving engine, supporting the driving triangle of biomarkers and liquid biopsy, AI in medical imaging, and regenerative medicine with novel drug delivery. Cancer immunotherapy is a specialized, mature domain, while gene editing (CRISPR), nanomedicine, and the microbiome shape future frontiers. Clinical translation requires accelerating mature technologies, establishing national genomic databases, and strengthening interdisciplinary synergies to achieve precise, patient-centered, preventive treatments.