开发一种使用语言处理技术的方法,用于提取有关药物-健康食品相互作用的信息
Mari Yoshizaki1,2, Yuki Kuriya2, Masaki Yamamoto2
1Biological Science and Technology, Life and Materials Systems Engineering, Graduate School of Advanced Technology and Science, Tokushima University, Tokushima City, Tokushima Prefecture, Japan.
British journal of clinical pharmacology
|March 20, 2024
概括
这项研究开发了一种工作流程,使用网络分析和生物医学背景来确定药物健康食品相互作用 (DHIs). 工作流程有效地提取已知和潜在未知DHIs,提高药物安全性.
科学领域:
- 药理学和生物信息学 药理学和生物信息学
- 药物与食物的相互作用
- 计算生物学 计算生物学
背景情况:
- 健康食品 (HFPs) 可能会引起不良药物相互作用.
- 关于药物-HFP相互作用 (DHIs) 的信息对于患者安全至关重要.
- 现有 DHI 的资源往往是分散的.
研究的目的:
- 建立一个高效的工作流程,从开放资源中提取药物-HFP相互作用 (DHIs).
- 整合网络分析和生物医学背景用于DHI预测.
- 为了识别已知和潜在未知DHIs.
主要方法:
- 从公共数据库和文献中收集了关于药物,酶,相互作用和已知的DHI的数据.
- 构建了酶,HFP和药物的网络,确定了酶作为相互作用中心.
- 应用 BioWordVec 来分析生物医学背景并预测潜在的 DHI.
主要成果:
- 在最初的网络分析中确定了44,965个DHI (30%已知).
- 方法2-1通过专注于酶特异性HFPs,获得7401个DHI (17%已知).
- 方法2-2通过选择具有与药物类似功能的HFPs来确定2819个DHI (30%已知).
结论:
- 成功构建了一个结合语言处理和网络分析的集成工作流.
- 这种工作流允许高效地提取各种已知和未知的DHI.
- 开发的方法有助于识别潜在的药物-健康食品相互作用.
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