A review article on "AI-guided discovery of novel anti-inflammatory agents for cancer therapy: A new era in drug development"
Vivek Paithankar, Deepika Devnani, Trupti A. Nimburkar · Intelligent Hospital · 2025
ABSTRACT Artificial intelligence (AI) is transforming anti-inflammatory drug discovery for cancer therapy by enabling data-driven exploration of complex biological systems. This review highlights how AI techniques—including deep learning, quantitative structure-activity relationship (QSAR) modeling, and multi-omics integration—facilitate the identification, repurposing, and optimization of compounds targeting key inflammatory pathways such as NF-κB, STAT3, COX-2, and the IL-6/JAK axis. By leveraging high-throughput data from genomics, proteomics, and metabolomics, AI enhances target prediction, compound screening, and patient stratification with unprecedented speed and precision. The novelty of this review lies in its focused analysis of how AI intersects with inflammation biology to unlock new therapeutic strategies in oncology. We also examine critical challenges facing AI implementation, including data heterogeneity, lack of standardization, and difficulties in biological validation. Ethical concerns around transparency, privacy, and bias are discussed in the context of clinical deployment. Despite these hurdles, AI offers a powerful framework to overcome limitations of traditional drug development—such as high attrition rates, low throughput, and static hypothesis-driven models—by enabling adaptive, scalable, and integrative discovery pipelines. Ultimately, AI holds promise to reshape inflammation-targeted therapy through personalized, predictive, and precision-based approaches. This review uniquely integrates recent advances in AI models with inflammation-specific pathways in cancer, offering a focused perspective on precision drug discovery.”