药物识别和验证中的人工智能:一个范围审查
Mukhtar Lawal Abubakar1, Neha Kapoor1, Asha Sharma2
1School of Applied Sciences, Suresh Gyan Vihar University, Jaipur, Rajasthan, India.
Drug research
|June 3, 2024
概括
人工智能 (AI) 正在通过简化漫长,昂贵和低效的过程来改善药物发现. 这项研究审查了AI在药物发现中的应用,确定了研究缺口,并提出了未来的机会.
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.
- 生物技术是生物技术.
背景情况:
- 药物发现是一个复杂,漫长和昂贵的过程,其消耗率很高.
- 提高效率,减少时间和成本对于制药行业至关重要.
- 人工智能 (AI) 提供了潜在的解决方案,以增强药物发现的各个阶段.
研究的目的:
- 审查近期基于人工智能的药物发现模型.
- 识别需要进一步关注的阶段.
- 将人工智能方法分类并提出未来的研究方向.
主要方法:
- 在多个电子数据库 (Scopus,PubMed,MEDLINE等) 进行系统的文献搜索. 从2016年1月开始到2023年9月.
- 使用标准化表格提取数据.
- 分析提取的数据以确定趋势和研究机会.
主要成果:
- 在不同药物发现阶段识别众多人工智能应用.
- 突出特定的阶段,这些阶段将受益于人工智能专注的增加.
- 开发用于药物发现的AI方法的分类学.
结论:
- 人工智能是药物发现的变革性技术,在效率和成功率上提供了显著的改进.
- 需要在特定领域进行进一步的研究,以充分利用人工智能的潜力.
- 这项研究为未来人工智能驱动的药物发现研究提供了路线图.
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