从肿瘤诊断篮子到 N-of-1 平台试验和真实世界数据:改变精准肿瘤学临床试验设计

IF 9.6 1区 医学 Q1 ONCOLOGY Cancer treatment reviews Pub Date : 2024-03-04 DOI:10.1016/j.ctrv.2024.102703
Elena Fountzilas , Apostolia-Maria Tsimberidou , Henry Hiep Vo , Razelle Kurzrock
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引用次数: 0

摘要

通过先进的基因组测序和多组学分析,为合适的患者选择合适的药物,这就是精准癌症医学。传统的癌症临床试验设计遵循定义明确的方案,评估新疗法在患者群体中的疗效,患者群体通常根据恶性肿瘤的组织学/原发组织来确定。相比之下,精准医学则寻求优化个体患者的获益,即确定获益者而非整体获益者。由于癌症是一种由分子改变驱动的疾病,创新的试验设计,包括生物标志物定义的肿瘤诊断篮子试验,正在推动突破性的监管审批和基因与免疫靶向药物的应用。分子检测进一步揭示了一个颠覆性的现实,即晚期癌症异常复杂且各不相同。因此,优化治疗往往需要药物组合和N-of-1定制,而新一代的N-of-1试验可以解决这一问题。真实世界数据和结构化主登记试验也提供了海量数据集,进一步推动了肿瘤学的变革。最后,机器学习正在促进快速发现,在不久的将来,高通量计算、建模和三维打印可能会用于实时发现和设计定制药物。
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Tumor-agnostic baskets to N-of-1 platform trials and real-world data: Transforming precision oncology clinical trial design

Choosing the right drug(s) for the right patient via advanced genomic sequencing and multi-omic interrogation is the sine qua non of precision cancer medicine. Traditional cancer clinical trial designs follow well-defined protocols to evaluate the efficacy of new therapies in patient groups, usually identified by their histology/tissue of origin of their malignancy. In contrast, precision medicine seeks to optimize benefit in individual patients, i.e., to define who benefits rather than determine whether the overall group benefits. Since cancer is a disease driven by molecular alterations, innovative trial designs, including biomarker-defined tumor-agnostic basket trials, are driving ground-breaking regulatory approvals and deployment of gene- and immune-targeted drugs. Molecular interrogation further reveals the disruptive reality that advanced cancers are extraordinarily complex and individually distinct. Therefore, optimized treatment often requires drug combinations and N-of-1 customization, addressed by a new generation of N-of-1 trials. Real-world data and structured master registry trials are also providing massive datasets that are further fueling a transformation in oncology. Finally, machine learning is facilitating rapid discovery, and it is plausible that high-throughput computing, in silico modeling, and 3-dimensional printing may be exploitable in the near future to discover and design customized drugs in real time.

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来源期刊
Cancer treatment reviews
Cancer treatment reviews 医学-肿瘤学
CiteScore
21.40
自引率
0.80%
发文量
109
审稿时长
13 days
期刊介绍: Cancer Treatment Reviews Journal Overview: International journal focused on developments in cancer treatment research Publishes state-of-the-art, authoritative reviews to keep clinicians and researchers informed Regular Sections in Each Issue: Comments on Controversy Tumor Reviews Anti-tumor Treatments New Drugs Complications of Treatment General and Supportive Care Laboratory/Clinic Interface Submission and Editorial System: Online submission and editorial system for Cancer Treatment Reviews
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