Session Introduction: Drug-repurposing and discovery in the era of "big" real-world data: how the incorporation of observational data, genetics, and other -omic technologies can move us forward.

Megan M. Shuey, J. Hellwege, Nikhil Khankari, Marijana Vujkovic, Todd L. Edwards
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Abstract

This PSB 2024 session discusses the many broad biological, computational, and statistical approaches currently being used for therapeutic drug target identification and repurposing of existing treatments. Drug repurposing efforts have the potential to dramatically improve the treatment landscape by more rapidly identifying drug targets and alternative strategies for untreated or poorly managed diseases. The overarching theme for this session is the use and integration of real-world data to identify drug-disease pairs with potential therapeutic use. These drug-disease pairs may be identified through genomic, proteomic, biomarkers, protein interaction analyses, electronic health records, and chemical profiling. Taken together, this session combines novel applications of methods and innovative modeling strategies with diverse real-world data to suggest new pharmaceutical treatments for human diseases.
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会议简介:大 "真实世界数据时代的药物再利用和发现:观察数据、遗传学和其他原子技术如何推动我们前进。
本次 PSB 2024 会议将讨论目前用于治疗药物靶点识别和现有疗法再利用的许多广泛的生物、计算和统计方法。通过更快速地确定药物靶点和针对未治疗或治疗效果不佳疾病的替代策略,药物再利用工作有可能极大地改善治疗状况。本次会议的首要主题是使用和整合真实世界的数据,以确定具有潜在治疗用途的药物-疾病配对。这些药物-疾病配对可通过基因组、蛋白质组、生物标记物、蛋白质相互作用分析、电子健康记录和化学特征分析来确定。总之,本讲座将新方法的应用和创新建模策略与各种真实世界数据相结合,为人类疾病提出新的药物治疗建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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FedBrain: Federated Training of Graph Neural Networks for Connectome-based Brain Imaging Analysis. Generating new drug repurposing hypotheses using disease-specific hypergraphs. Impact of Measurement Noise on Genetic Association Studies of Cardiac Function. Imputation of race and ethnicity categories using genetic ancestry from real-world genomic testing data. intCC: An efficient weighted integrative consensus clustering of multimodal data.
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