Deciphering HIV Pathogenesis: A Deep Dive into Viral Entry, Immune Evasion, and Host Responses in HIV infection and novel aspects of AI/ML in HIV research

This comprehensive literature review provides an overview on the variety  mechanisms of HIV-1 pathogenesis, focusing on viral entry, immune evasion strategies, and the host immune responses. This review presents a summary of  HIV initial invasion processes, detailing how HIV utilizes CD4+ T cells, macrophages, and dendritic cells, and the critical roles of co-receptors CCR5 and CXCR4 in mediating viral entry. The review dissects the sophisticated mechanisms by virus to evade immune system, including the formation of viral reservoirs, mutations, and the induction of immune exhaustion, highlighting the persistent challenge of HIV latency and  implications for cure strategies.

This review explores the dynamic of immune responses towards HIV infection, including the activation and depletion of CD4+ T cells, the compensatory mechanisms of CD8+ T cell responses, and the paradoxical effects of chronic immune activation on disease progression. Diving in to recent findings, to identify the gaps in our understanding of the long-term effects of HIV on the immune system, underscoring the need for innovative therapeutic interventions to disrupt viral reservoirs and counteract immune dysfunction.

A novel aspect of this review is the exploration of artificial intelligence (AI) and machine learning (ML) as transformative tools in HIV research. How AI/ML techniques are being applied to predict viral evolution, identify new therapeutic targets, and optimize treatment regimens. The potential of AI/ML to personalize patient treatment and interpret complex data from clinical trials is highlighted, offering promising avenues for enhancing the efficacy of antiretroviral therapy and advancing towards the ultimate goal of an HIV cure.

This review aims to provide a thorough review of current knowledge on HIV pathogenesis, immune response challenges, and the groundbreaking potential of AI and ML in paving new directions for research and therapy in the fight against HIV/AIDS.