数据科学在药物发现安全方面:挑战和机遇
Nicholas J Coltman1, Ruth A Roberts1,2, James E Sidaway1
1ApconiX, Alderley Edge, Cheshire SK10 4TG, UK.
Experimental biology and medicine (Maywood, N.J.)
|December 8, 2023
概括
早期药物向安全评估 (TSA) 对项目成功至关重要. 一种新的数据科学方法整合了各种数据以获得最佳的TSA,在药物开发的早期识别和减轻风险.
科学领域:
- 药物的发现和开发.
- 药理学和毒理学 药理学和毒理学
- 生物信息学和数据科学
背景情况:
- 早期降低药物目标和化学的风险对于成功的药物项目至关重要.
- 目标安全评估 (TSA) 整合复杂的数据 (生物学,遗传学,表达,竞争对手情报) 来评估目标调制的安全风险.
- 每天涌入的新信息需要对全面的TSA进行高效的数据处理.
研究的目的:
- 开发一种基于数据科学的方法,用于获取相关证据,以优化目标安全评估 (TSA).
- 在药物发现项目中早期识别和减轻潜在的安全风险.
- 引导药物开发的关键早期决策,包括目标选择和实验设计.
主要方法:
- 专家领导的传统和基于人工智能 (AI) 的文献和生物信息数据库挖掘.
- 开发一个数据科学框架,用于获取和分析证据.
- 应用一个根据目标新性调整的证据框架,以确定潜在的安全风险.
主要成果:
- 以数据科学为基础的方法可以有效地获取最佳TSA的证据.
- 使用结构化证据框架识别潜在的安全风险.
- 专家的解释对于对药物安全性,模式和患者群体的细微了解至关重要.
结论:
- 运输安全局利用数据科学进步,提高药物项目的知情决策和资源管理.
- 这些TSA的早期应用指导了关键决策,如目标选择,化学和体外/体内研究设计.
- 这种方法通过主动识别和减轻安全风险,最大限度地提高了药物项目成功的潜力.
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