Artificial Intelligence and Machine Learning Approaches in Designing Immunotherapy in Cancer

Artificial intelligence (AI) and machine learning (ML) are revolutionizing cancer immunotherapy by addressing the complex interplay between cancer and the immune system. This chapter explores how AI technologies enhance immunotherapy development across multiple domains: antibody design, response prediction, biomarker identification, and T-cell target discovery. In therapeutic antibody design, AI improves efficiency through predictive modeling of antibody-antigen interactions, structure prediction tools, generative models that create novel antibody sequences, and developability optimization. Clinical applications include AI-powered systems that predict immunotherapy responses using multi-omics data integration, helping distinguish pseudoprogression from true disease progression. Beyond conventional biomarkers like programmed cell death protein 1, AI enables identification of additional markers including tumor mutational burden, microsatellite instability, immune cell infiltration patterns, and novel genomic alterations. Multi-omics approaches leverage AI to synthesize diverse data types, uncovering complex biomarker signatures that more accurately predict treatment outcomes. For T-cell target identification, next-generation immunoediting platforms like Gritstone's EDGE™ system exemplify AI-powered approaches that precisely identify neoantigens by integrating sequencing technologies with sophisticated prediction algorithms (Table 2.1). These platforms support both personalized and shared antigen approaches to immunotherapy, potentially enhanced through integration with innate immune pathways. Despite remarkable progress, challenges persist in addressing tumor heterogeneity, immune evasion mechanisms, and technical limitations in prediction algorithms. The continued refinement of AI approaches, expansion to diverse cancer types, and integration with complementary therapeutic modalities represent promising future directions. Overall, AI and ML are poised to transform cancer immunotherapy by enabling more precise, effective, and personalized treatment approaches that harness the immune system's power against cancer.