量化结构-活动关系模型用于预测心脏不良影响
Zhongyu Mou1, Patra Volarath1, Rebecca Racz1
1FDA Center for Drug Evaluation and Research (CDER), Silver Spring, Maryland 20903, United States.
新模型预测药物诱导的心脏毒性,这是药物开发失败的主要原因. 这些工具评估各种心脏风险,帮助药物发现和安全性评估.
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
- 计算化学的计算化学
背景情况:
- 药物诱导的心脏毒性是药物候选人在开发过程中消耗的重要因素.
- 早期和准确的心脏毒性评估对于监管部门的批准至关重要.
研究的目的:
- 开发各种药物诱导的心脏不良事件的预测模型.
- 加强在临床前和临床阶段对候选药物的安全性评估.
主要方法:
- 从FDA 2002年药物不良事件报告系统中提取了市场上市后的不良事件数据.
- 使用了243个与心脏毒性相关的首选术语,分为12个临床相关的类别.
- 采用两个商业定量结构-活动关系 (QSAR) 平台来构建预测模型.
主要成果:
- 开发了12个模型,涵盖了各种心脏终点,如心脏骤停,心力衰竭和心律不整.
- 在交叉验证中达到高达80%的灵敏度和80%的负预测性.
- 集成多个数据源,包括药物标签,文献和临床数据.
结论:
- 开发的QSAR模型提供了快速,可靠和全面的心脏毒性预测.
- 这些模型可以在药物发现和监管安全评估过程中显著帮助.
- 有助于在发育早期识别潜在的心脏毒性化合物.
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