抗体药物偶联物、放射性偶联物、T细胞接合剂和嵌合抗原受体细胞疗法等新型治疗剂的结合代表了肿瘤学的范式转变。细胞表面靶标定量、受体内化的定量评估以及肿瘤微环境 (TME) 的变化是开发用于患者选择和治疗反应的生物标志物的重要变量。评估这些参数需要超越基于免疫组织化学、原位杂交和/或测序测定的传统生物标志物方法的能力。计算病理学正在成为这一新治疗领域的变革性解决方案，不仅可以详细评估靶标的存在、表达水平和肿瘤内分布，还可以详细评估肿瘤细胞及其周围 TME 的其他表型特征。在这里，我们描述了计算病理学在增强这些先进疗法的功效和特异性方面的关键作用，强调了新颖的人工智能模型的整合，这些模型有望彻底改变生物标志物的发现和药物开发。© 2024 作者。约翰·威利出版的《分子肿瘤学》

The incorporation of novel therapeutic agents such as antibody-drug conjugates, radio-conjugates, T-cell engagers, and chimeric antigen receptor cell therapies represents a paradigm shift in oncology. Cell-surface target quantification, quantitative assessment of receptor internalization, and changes in the tumor microenvironment (TME) are essential variables in the development of biomarkers for patient selection and therapeutic response. Assessing these parameters requires capabilities that transcend those of traditional biomarker approaches based on immunohistochemistry, in situ hybridization and/or sequencing assays. Computational pathology is emerging as a transformative solution in this new therapeutic landscape, enabling detailed assessment of not only target presence, expression levels, and intra-tumor distribution but also of additional phenotypic features of tumor cells and their surrounding TME. Here, we delineate the pivotal role of computational pathology in enhancing the efficacy and specificity of these advanced therapeutics, underscoring the integration of novel artificial intelligence models that promise to revolutionize biomarker discovery and drug development.© 2024 The Author(s). Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.