使用FAERS数据库探索预测PXR激活剂的不良事件关联
Saki Yamada1, Yoshihiro Uesawa1
1Department of Medical Molecular Informatics, Meiji Pharmaceutical University, Tokyo 204-8588, Japan.
孕妇X受体 (PXR) 的激活与心脏风险有关. 机器学习识别了与心血管不良事件相关的药物中的PXR激活活性,有助于药物安全性评估.
科学领域:
- 药理学 药理学是指药理学的学科.
- 毒理学 毒理学 毒理学
- 计算生物学 计算生物学
背景情况:
- 孕妇X受体 (PXR) 是一个调节药物代谢和生理功能的核受体.
- 对于PXR激活对不良事件的全部影响仍然不完全理解.
- 在药物诱导的毒性中PXR的作用需要进一步的研究.
研究的目的:
- 开发一种机器学习模型,用于预测PXR激活剂活性.
- 评估PXR激活剂活性与药物不良事件之间的关联.
- 为了确定与PXR激活相关的潜在心血管风险.
主要方法:
- 开发了一种机器学习模型来预测PXR激进剂活性.
- 将模型应用于美国食品和药物管理局不良事件报告系统 (FAERS) 数据库中的药物.
- 分析了使用统计风险评估 (lnROR, -logp) 对报告的不良事件的预测PXR激动剂药物相互作用.
主要成果:
- 机器学习模型成功预测了PXR激活剂活性.
- 对多种心脏疾病的统计学上显著的风险被确定为PXRagonist-active药物.
- 特定的药物心脏事件相关性显示出高风险概况.
结论:
- PXR激活与心血管不良影响有关.
- 机器学习模型可以帮助预测药物诱导的心血管风险.
- 早期识别PXR介导的风险可以提高药物安全性评估.
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