向药物发现方向推进人工智能:工具,技术和应用
Peter Chinedu Agu1, Chidiebere Nwiboko Obulose2
1Department of Biochemistry, College of Science, Evangel University, Akaeze, Ebonyi State, Nigeria.
Drug development research
|February 20, 2024
概括
人工智能 (AI) 正在通过提供比传统方法更快,更便宜的方法来彻底改变药物开发. 这项技术加速了新疗法的发现,并提高了创造新药的效率.
科学领域:
- 计算化学是一种计算化学.
- 药理学 药理学是指药理学的学科.
- 药物发现 药物发现
背景情况:
- 传统药物开发是漫长而昂贵的.
- 人工智能 (AI) 为优化药物发现管道提供了变革潜力.
- 数据驱动的方法在药物研究中越来越重要.
研究的目的:
- 审查人工智能 (AI) 方法对药物开发的影响.
- 探索AI模型和数据资源如何提高药物发现的效率和成本效益.
- 突出人工智能在加速创建新疗法方面的作用.
主要方法:
- 药物开发信息来源的概述.
- 讨论用于AI兼容性的分子表示技术.
- 对用于药物发现模型创建的人工智能算法的审查.
- 在预测药物毒性,生物活性和性质方面探索人工智能应用.
- 详细检查人工智能模型用于新药设计和药物向相互作用.
- 人工智能在纳米医学中的覆盖范围和协同/对抗效应预测.
主要成果:
- 人工智能显著提高了对药物特性,毒性和生物活性的预测.
- 人工智能模型在新药设计和预测药物向相互作用方面表现出有效性.
- 人工智能促进了先进的应用,例如纳米医药设计和药物协同效应预测.
- 人工智能集成为传统药物开发提供了更实惠,更方便的替代方案.
结论:
- 人工智能有可能极大地加速和提高药物发现的效率.
- 人工智能有助于开发新的和改进的药物.
- 需要进一步的研究和开发,以充分利用AI在药物发现方面的能力,并克服现有的挑战.
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