{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T06:15:10Z","timestamp":1779344110520,"version":"3.51.4"},"reference-count":32,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T00:00:00Z","timestamp":1756512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The phosphoinositide 3-kinase (PI3K)\/AKT signaling pathway is a crucial regulator of cellular metabolism, proliferation, and survival. It is frequently dysregulated in metabolic, cardiovascular, and neoplastic disorders. Despite the advancements in multi-omics technology, existing methods often fail to provide real-time, pathway-specific insights for precision medicine and drug repurposing. We offer Agentic RAG-Driven Multi-Omics Analysis (ARMOA), an autonomous, hypothesis-driven system that integrates retrieval-augmented generation (RAG), large language models (LLMs), and agentic AI to thoroughly analyze genomic, transcriptomic, proteomic, and metabolomic data. Through the use of graph neural networks (GNNs) to model complex interactions within the PI3K\/AKT pathway, ARMOA enables the discovery of novel biomarkers, probable candidates for drug repurposing, and customized therapy responses to address the complexities of PI3K\/AKT dysregulation in disease states. ARMOA dynamically gathers and synthesizes knowledge from multiple sources, including KEGG, TCGA, and DrugBank, to guarantee context-aware insights. Through adaptive reasoning, it gradually enhances predictions, achieving 91% accuracy in external testing and 92% accuracy in cross-validation. Case studies in breast cancer and type 2 diabetes demonstrate that ARMOA can identify synergistic drug combinations with high clinical relevance and predict therapeutic outcomes specific to each patient. The framework\u2019s interpretability and scalability are greatly enhanced by its use of multi-omics data fusion and real-time hypothesis creation. ARMOA provides a cutting-edge example for precision medicine by integrating multi-omics data, clinical judgment, and AI agents. Its ability to provide valuable insights on its own makes it a powerful tool for advancing biomedical research and treatment development.<\/jats:p>","DOI":"10.3390\/a18090545","type":"journal-article","created":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T12:04:28Z","timestamp":1756814668000},"page":"545","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Agentic RAG-Driven Multi-Omics Analysis for PI3K\/AKT Pathway Deregulation in Precision Medicine"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9418-5346","authenticated-orcid":false,"given":"Micheal Olaolu","family":"Arowolo","sequence":"first","affiliation":[{"name":"Department of Public Health Sciences, Health Informatics Program, Xavier University of Louisiana, New Orleans, LA 70461, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sulaiman Olaniyi","family":"Abdulsalam","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Kwara State University, Malete 241104, Nigeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafiu Mope","family":"Isiaka","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Kwara State University, Malete 241104, Nigeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0512-7089","authenticated-orcid":false,"given":"Kingsley Theophilus","family":"Igulu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Kenule Beeson Saro-Wiwa Polytechnic, Bori 502101, Nigeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bukola Fatimah","family":"Balogun","sequence":"additional","affiliation":[{"name":"School of Computer Science and Informatics, Demontfort University, Leicester LE1 9BH, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6145-8096","authenticated-orcid":false,"given":"Mihail","family":"Popescu","sequence":"additional","affiliation":[{"name":"Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA"},{"name":"Department of Biomedical Informatics, Biostatistics and Medical Epidemiology, School of Medicine, University of Missouri, Columbia, MO 65211, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4809-0514","authenticated-orcid":false,"given":"Dong","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Kwara State University, Malete 241104, Nigeria"},{"name":"Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA"},{"name":"Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA"},{"name":"Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1038\/s41392-021-00828-5","article-title":"Targeting PI3K\/Akt signal transduction for cancer therapy","volume":"6","author":"He","year":"2021","journal-title":"Signal Transduct. 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