全球制药业洞察 | AI或可提升诊断水平，帮助实现肿瘤治疗个性化

Core Viewpoint - The article discusses the potential of AI to enhance diagnostic capabilities and facilitate personalized cancer treatment, emphasizing the integration of AI with clinical data and emerging biomarkers [3][7]. Group 1: AI in Cancer Diagnosis - AI is increasingly being utilized in the analysis of tissue pathology slides, with advancements in computational power and data transmission speed driving broader applications in diagnostics [4]. - The use of AI in radiology, particularly for prostate cancer, is highlighted as a promising area, aiming to reduce the burden of invasive biopsy procedures [4][7]. Group 2: Personalized Cancer Treatment - The next frontier for AI in cancer treatment involves tracking tumor changes over time to enable personalized therapy, with companies like Tempus and Flatrion Health building large clinical outcome datasets for AI model training [7]. - AI's application in personalized treatment aligns with the recent "Gateway" infrastructure initiative in the U.S., which identifies healthcare as a primary application area for expanded data centers [7]. Group 3: Emerging Biomarkers - Circulating tumor DNA (ctDNA) is identified as a significant emerging biomarker, with potential uses in early detection and tracking treatment responses, although questions remain regarding its clinical implementation [9]. - The expectation is set for ctDNA sequencing to explore potential resistance mechanisms during disease progression, guiding subsequent treatment options [9].