Karamello Halak, Yuseph Mohamed, Armantas Gintautas
Abstract
Pembrolizumab and nivolumab are examples of immune checkpoint inhibitors (ICIs) drugs that are cancer treating drugs that reactivate antitumor immune responses. But they result in immune related side effects (irAEs) that are typically multisystemic and unpredictable. In additionally referring to advanced artificial intelligence (machine learning) for early detection and more effective therapeutic management, this research outlines the pathophysiology and associated risk factors of irAEs. The findings show that genetics (HLA), tumour environment, specific gut bacteria and cytokine hyperactivation most notably TNFα, IL6 and IFNγ significantly affect the severity of irAE. To accomplish immunotherapy efficacy and safety, cytokine analysis, DNA testing and microbiome modification must be used in combination in treatments. Future studies have to involve AI prediction models and multifactor integration.
Keyword(s): Pembrolizumab, Nivolumab, Immune related adverse events, Cytokine storm, HLA, Tumor microenvironment, Microbiome, Machine learning, Immunotherapy, Cancer.
DOI: 10.35988/sm-hs.2025.313
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