人工智能方法用于药物标的发现和验证
Aaron Wenteler1,2,3, Claudia P Cabrera1,2,4, Wei Wei3
1Digital Environment Research Institute, Queen Mary University of London, London, United Kingdom.
Cambridge prisms. Precision medicine
|September 11, 2024
概括
人工智能 (AI) 通过从各种数据中预测药物标性质来加速药物发现. 人工智能模型验证和数据偏差对于新型药物开发仍然存在挑战.
科学领域:
- 生物化学 生物化学
- 药理学 药理学是指药理学的学科.
- 计算生物学 计算生物学
背景情况:
- 人工智能 (AI) 正在彻底改变制药研究.
- 人工智能集成为增强药物发现管道提供了巨大的潜力.
- 目标的发现和验证是开发新药的关键早期阶段.
研究的目的:
- 审查人工智能在药物标发现中的当前应用.
- 探索人工智能的未来潜力,用于识别和验证药物点.
- 突出AI驱动药物开发的挑战和机遇.
主要方法:
- 整合不同的生物数据模式.
- 人工智能驱动的药物标属性的预测.
- 对用于药物发现的AI算法近期进展的分析.
主要成果:
- 人工智能能够准确地预测药物向性质.
- 人工智能揭示了疾病的生物机制.
- 人工智能指导药物发现中的战略决策.
结论:
- 人工智能在加速和改进药物发现方面显示出巨大的前景.
- 克服数据偏差和模型解释性等挑战至关重要.
- 人工智能正在为新和更安全的制药生产铺平道路.
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