{"id":573,"date":"2026-08-11T19:55:18","date_gmt":"2026-08-11T19:55:18","guid":{"rendered":"https:\/\/syrian-biomedica.com\/salma-daher\/"},"modified":"2026-08-15T09:08:25","modified_gmt":"2026-08-15T09:08:25","slug":"salma-daher","status":"publish","type":"page","link":"https:\/\/syrian-biomedica.com\/ar\/salma-daher\/","title":{"rendered":"Salma Daher"},"content":{"rendered":"

Salma Daher<\/strong><\/h1>\n

Layth Khalid Qays, Sally S. Alma\u2019ani, Razan S. AL Shehadeh, Salma M. Al Daher, Hala M. Alzeer and Fadi G. Saqallah*<\/p>\n

Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan, 11733 Amman, Jordan<\/h1>\n

\n

Artificial Intelligence for Precision Medicine in Melanoma: Advances in Biomarker Discovery, Immunotherapy, and Personalized Neoantigen Vaccines<\/strong><\/p>\n<\/div>\n

\n

Background<\/u>:<\/strong><\/p>\n

Melanoma is one of the most aggressive malignancies owing to its high metastatic potential, tumor heterogeneity, and variable responses to immunotherapy. Recent advances in artificial intelligence (AI) and machine learning (ML) have enabled analysis of complex multi-omics data, facilitating biomarker discovery, therapeutic response prediction, and precision oncology. However, AI-driven personalized medicine strategies in melanoma have not been comprehensively synthesized.<\/p>\n<\/p>\n

Objectives<\/u>:<\/strong><\/p>\n

To systematically evaluate recent AI applications in precision melanoma medicine, focusing on biomarker discovery, immunotherapy response prediction, personalized neoantigen vaccine development, and their clinical relevance.<\/p>\n<\/p>\n

Methods<\/u>:<\/strong><\/p>\n

A systematic review of peer-reviewed PubMed studies published over the past five years was conducted. Ten eligible studies investigating clinically validated AI applications in melanoma were included. Evidence was synthesized on machine learning, deep learning, multi-omics integration, genomic and transcriptomic profiling, single-cell RNA sequencing, and AI-driven analytical frameworks for diagnosis, prognosis, biomarker identification, treatment-response prediction, and personalized immunotherapy.<\/p>\n<\/p>\n

Results<\/u>:<\/strong><\/p>\n

The reviewed studies demonstrated that AI enhances precision melanoma management through predictive modeling and multi-omics integration. Deep learning improved prediction of immune checkpoint inhibitor response by integrating genomic, transcriptomic, and mutation profiles. A 15-gene predictive model, validated across eight independent patient cohorts, accurately identified biomarkers associated with immunotherapy response. Single-cell transcriptomic analyses revealed prognostic signatures linked to tumor heterogeneity, metastasis, and disease progression. The Cross-Platform Omics Prediction (CPOP) framework identified transferable biomarkers while reducing platform-specific bias. AI-driven genomic analyses also facilitated personalized neoantigen discovery and improved prediction of lymph node metastasis, supporting patient stratification and individualized treatment.<\/p>\n<\/p>\n

Conclusion<\/u>:<\/strong><\/p>\n

Artificial intelligence is transforming precision melanoma medicine by improving biomarker discovery, prognostic assessment, patient stratification, immunotherapy response prediction, and personalized neoantigen vaccine development. Nevertheless, challenges related to data heterogeneity, model generalizability, external validation, and ethical implementation remain. Future research should emphasize explainable AI, robust multi-omics integration, and interdisciplinary collaboration to accelerate clinical translation.<\/p>\n<\/p>\n

Keywords<\/u>:<\/strong><\/p>\n

Artificial intelligence; Melanoma; Precision medicine; Immunotherapy; Neoantigen vaccines<\/p>\n<\/div>\n


\n<\/p>\n","protected":false},"excerpt":{"rendered":"

Salma Daher Layth Khalid Qays, Sally S. Alma\u2019ani, Razan S. AL Shehadeh, Salma M. Al Daher, Hala M. Alzeer and Fadi G. Saqallah* Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan, 11733 Amman, Jordan Artificial Intelligence for Precision Medicine in Melanoma: Advances in Biomarker Discovery, Immunotherapy, and Personalized Neoantigen Vaccines Background: Melanoma is […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_et_pb_custom_css":""},"class_list":["post-573","page","type-page","status-publish","hentry"],"_et_pb_custom_css":"","_links":{"self":[{"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/pages\/573","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/comments?post=573"}],"version-history":[{"count":2,"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/pages\/573\/revisions"}],"predecessor-version":[{"id":610,"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/pages\/573\/revisions\/610"}],"wp:attachment":[{"href":"https:\/\/syrian-biomedica.com\/ar\/wp-json\/wp\/v2\/media?parent=573"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}