From Small Molecules to Degraders and AI: Contemporary Trends and Future Directions in Anticancer Drug Discovery

Cancer remains one of the leading causes of death worldwide, demanding continuous innovation in therapeutic strategies. Traditional chemotherapeutic agents, though effective in certain contexts, are limited by systemic toxicity, drug resistance, and non-specific targeting. Over the past two decades, the landscape of anticancer drug discovery has undergone a paradigm shift with the emergence of molecularly targeted agents, immunotherapies, and rational drug design technologies. Advancements in genomics, proteomics, and structural biology have enabled the identification of novel cancer-specific targets, while computational and artificial intelligence (AI)-driven approaches are accelerating lead optimization and predictive modeling of drug efficacy and toxicity. The development of antibody–drug conjugates (ADCs), bispecific antibodies, and targeted protein degraders (PROTACs) represents a new generation of therapies capable of addressing previously “undruggable” targets. Meanwhile, patient-derived organoids, 3D co-culture systems, and high-content screening platforms are refining preclinical evaluation and improving translational success rates. This review summarizes the recent trends in anticancer drug discovery, highlights the integration of computational and experimental pipelines, and explores emerging modalities poised to redefine cancer treatment in the coming decade. The future of anticancer drug discovery lies in combining precision oncology, AI-based design, and systems-level modeling to deliver safer, more effective, and personalized therapies against cancer’s molecular complexity.