Vázquez Nelson García, Nada Hossam, Upadhyay Saurabh, Gabr Moustafa T
Department of Radiology, Molecular Imaging Innovations Institute (MI3), Weill Cornell Medicine New York NY 10065 USA
RSC Adv. 2025 Aug 22;15(36):29937-29951. doi: 10.1039/d5ra03914b. eCollection 2025 Aug 18.
The development of immune therapeutics has revolutionized modern medicine, particularly in the treatment of cancer and autoimmune diseases. Historically, drug discovery has been guided by two main strategies: phenotypic and target-based approaches. While phenotypic screening has led to the identification of first-in-class therapies, targeted drug discovery has enabled rational drug design based on molecular mechanisms, enhancing precision and therapeutic efficacy. The integration of phenotypic and targeted approaches has been accelerated by advancements in computational modeling, artificial intelligence, and multi-omics technologies, and is reshaping drug discovery pipelines. Herein, key examples of immunomodulatory drugs, including immune checkpoint inhibitors, bispecific antibodies, and small-molecule modulators, are employed to highlight their discovery pathways and mechanisms of action. We also examine emerging hybrid approaches that connect functional and mechanistic insights to accelerate therapeutic development. Leveraging both paradigms, future immune drug discovery will depend on adaptive, integrated workflows that enhance efficacy and overcome resistance.
免疫疗法的发展彻底改变了现代医学，尤其是在癌症和自身免疫性疾病的治疗方面。从历史上看，药物研发主要受两种策略指导：表型筛选和基于靶点的方法。虽然表型筛选已促成了同类首创疗法的发现，但靶向药物研发已实现基于分子机制的合理药物设计，提高了精准度和治疗效果。计算建模、人工智能和多组学技术的进步加速了表型和靶向方法的整合，正在重塑药物研发流程。在此，免疫调节药物的关键实例，包括免疫检查点抑制剂、双特异性抗体和小分子调节剂，被用来突出它们的发现途径和作用机制。我们还研究了将功能和机制见解联系起来以加速治疗开发的新兴混合方法。利用这两种模式，未来的免疫药物研发将依赖于增强疗效并克服耐药性的适应性综合工作流程。
