案例研究:自然语言处理(NLP)与开放数据在胶质母细胞瘤治疗中的药物重新定位

2023 10th IEEE Swiss Conference on Data Science (SDS) Pub Date : 2023-06-01 DOI:10.1109/SDS57534.2023.00009

Curdin Marxer, Heiko Rölke, Alex Alfieri, M. Halatsch

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引用次数: 0

摘要

新药的开发和发现是一项长期、昂贵和冒险的努力，成功率很低。为现有药物或已知活性化合物确定新用途是一种众所周知的做法，称为“药物重新定位”或“药物重新定位”。本案例研究使用NLP技术和开放数据源，探索它们在确定胶质母细胞瘤治疗药物方面的潜力，而不是在DrugBank等已建立的数据库中记录的明显选择。

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Case Study: Natural Language Processing (NLP) with Open Data for Drug Repositioning in Glioblastoma Therapy

The development and discovery of new drugs is a long, costly and risky endeavour with low rate of success. It is a well-known practice to identify new uses for already existing drugs or known active compounds, referred to as “drug repositioning’’ or “drug repurposing This case study uses NLP techniques and open data sources to explore their potential in identifying drugs for glioblastoma therapy beyond the obvious choices documented in established databases like DrugBank.

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2023 10th IEEE Swiss Conference on Data Science (SDS)

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