ARTIFICIAL INTELLIGENCE BASED ANALYSIS OF THE ANTI-ARTHRITIC ACTIVITY OF POLYPHENOLS IN RHEUMATOID ARTHRITIS CELLULAR MODEL

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovial inflammation, leading to joint damage and functional impairment. The disease involves a complex interplay of genetic, environmental, and immunological factors, with pro-inflammatory cytokines such as TNF-α, IL-1, and IL-6 playing a pivotal role in disease progression. Current therapeutic strategies aim to mitigate inflammation and prevent joint destruction, but challenges remain due to adverse effects and incomplete responses to treatment.Polyphenols, naturally occurring compounds with anti-inflammatory and antioxidant properties, have emerged as potential therapeutic agents for RA. Studies suggest that polyphenols such as cur-cumin, resveratrol, EGCG, and quercetin modulate key inflammatory pathways, including NF-κB and MAPK, thereby reducing oxidative stress and immune dysregulation. However, their bioavail-ability and targeted delivery remain significant challenges. Nanoparticle-based drug delivery sys-tems offer a promising solution by enhancing polyphenol stability, improving bioavailability, and ensuring targeted delivery to inflamed synovial tissues. Various nanoparticles, including polymeric, liposomal, and metallic carriers, have been explored for optimizing RA treatment.Artificial intelligence (AI) and machine learning (ML) have revolutionized microscopic image anal-ysis in biomedical research, enabling precise detection and classification of synovial tissue altera-tions in RA. Deep learning models, particularly convolutional neural networks (CNNs), have demonstrated high accuracy in identifying pathological changes, facilitating early diagnosis and disease monitoring. Additionally, radiomic analysis, an advanced technique that extracts high-dimensional quantitative features from medical imaging data, has been explored for evaluating joint abnormalities and detecting synovial malignancies. By integrating AI-driven radiomic analysis with conventional imaging, clinicians can enhance diagnostic precision, assess disease severity, and im-prove personalized treatment strategies.This research explores the anti-arthritic potential of polyphenols, employing nanoparticles for tar-geted drug delivery, AI-based microscopic image analysis, and radiomic analysis for comprehen-sive disease assessment. The study aims to enhance therapeutic efficacy while minimizing adverse effects, providing novel insights into the application of advanced technologies in RA management.