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在OncoCTMiner:简化精确的瘤学试验匹配通过分子形状分析分析

Quan Xu^1,2, Yueyue Liu¹, Dawei Sun^1,2

¹Department of Bioinformatics, Beijing ChosenMed Clinical Laboratory Co. Ltd., Jinghai Industrial Park, 156 Jinghai 4th Road, Economic and Technological Development Area, Beijing 100176, China.

Database : the journal of biological databases and curation

|November 7, 2023

概括

精确瘤学需要有效的临床试验匹配. OncoCTMiner是一个自动化平台,分析试验标准和患者个人资料,以加快分子癌症临床试验的招生,改善患者获得向治疗的机会.

科学领域:

在瘤学瘤学.
生物信息学是一种生物信息学.
临床试验管理临床试验管理

背景情况:

精确瘤学依赖于癌症治疗的奥米克测序.
将患者与临床试验相匹配是复杂的,原因是大量的数据和严格的标准.
简化分子向疗法试验的患者招生是必不可少的.

研究的目的:

开发一个自动化的平台,OncoCTMiner,用于在分子癌症临床试验中预先选患者.
创建一个全面的精密瘤学资格标准数据库.
为了促进基于临床和遗传特征的患者试验匹配.

主要方法:

对2227个瘤学试验的资格标准的手动标记,以确定生物概念.
使用注释数据和生物医学NLP工具培训命名实体识别 (NER) 模型.
分析了460,952项临床试验,以提取精准医学概念和标准与试验关系.
开发一个患者试验匹配系统,与omics数据集成.

主要成果:

确定关键的生物概念 (癌症类型,基因,改变,药物,生物标志物,疗法).
创建一个全面的精确瘤学资格标准数据库.
分析显示了815万个精准医学概念和932万个实体-标准-试验三重体.
开发一个自动化的患者试验匹配系统.

结论:

OncoCTMiner自动化了分子癌症临床试验的预选.
该平台加快了患者获得精密瘤治疗的速度.
该系统提高了将患者与合适的临床试验相匹配的效率.

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