药物发现中的人工智能及其临床相关性
Rizwan Qureshi1,2, Muhammad Irfan3, Taimoor Muzaffar Gondal4
1College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Heliyon
|July 3, 2023
概括
人工智能 (AI) 通过分析大量的医疗数据来加速新药发现. 人工智能方法加快了开发速度,并预测了药物特性,降低了成本和管道中的故障.
科学领域:
- 生物技术是生物技术.
- 计算化学的计算化学
- 药理学 药理学是指药理学的学科.
背景情况:
- 随着COVID-19的爆发,人们越来越需要有效的药物发现.
- 传统药物开发是漫长的,昂贵的,容易失败的.
- 人工智能,计算能力和大数据的进步提供了新的解决方案.
研究的目的:
- 在药物发现管道中探索人工智能 (AI) 应用.
- 讨论AI在新药设计和财产预测中的作用.
- 审查人工智能驱动药物发现的挑战和机遇.
主要方法:
- 在药物发现阶段对人工智能应用的审查.
- 计算方法的讨论:图形神经网络,强化学习,生成模型.
- 基于结构的方法的探索:分子动力学,分子对接.
主要成果:
- 人工智能可以显著加快药物设计和财产预测.
- 开源数据库和人工智能工具促进了计算药物设计.
- 人工智能解决了分子表示,数据处理和标签方面的挑战.
结论:
- 人工智能为加速药物发现和开发提供了变革性的潜力.
- 解决数据和方法方面的挑战对于人工智能的成功至关重要.
- 对AI-生物技术初创企业的投资在该领域显示出有前途的进展.
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